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Abstract. The minimization of the wireless cost of tracking mobile users is a crucial issue in wireless networks. Some of the previous strategies addressing this issue leave an open gap, by requiring the use of information that is not generally available to the user (for example, the distance traveled by the user). For this reason, both the implementation of some of these strategies and the performance comparison to existing strategies is not clear. In this work we propose to close this gap by the use of Cell Identification Codes (CIC) for tracking mobile users. Each cell periodically broadcasts a short message which identifies the cell and its orientation relatively to other cells in the network. This information is used by the users to efficiently update their location. We propose several cell identification encoding schemes, which are used to implement different tracking strategies, and analyze the amount of information required by each tracking strategy. One of our major results is that there is no need to transmit a code which is unique for each cell. For example, a 3 bits CIC is sufficient to implement a distance-based tracking strategy in a two-dimensional system. In addition, we propose a combination of timer and movement tracking strategy, based on either a one-bit or a two-bit CIC, depending on system topology and user mobility. An important property of our framework is that the overall performance cost, and hence its comparison to existing methods, is evaluated for each tracking strategy. The CIC-based strategies are shown to outperform the geographic-based method currently used in existing networks, and the timer-based method, over a wide range of parameters. Moreover, this superiority increases as the number of users per cell increases.

Abstract-The issue of tracking a group of users is discussed in this study. Given the condition that the search is over only after all the users in the group are found, this problem is called the Conference Call Search (CCS) problem. The goal is to design efficient CCS strategies under delay and bandwidth constraints. While the problem of tracking a single user has been addressed by many studies, to the best of our knowledge, this study is one of the first attempts to reduce the search cost for multiple users. Moreover, as oppose to the single user tracking, for which one can always reduce the expected search delay by increasing the expected search cost, for a multiple users search the dependency between the delay and the search cost is more complicated, as demonstrated in this study. We identify the key factors affecting the search efficiency, and the dependency between them and the search delay. Our analysis shows that under tight bandwidth constraints, the CCS problem is NP-hard. We therefore propose a search method that is not optimal, but has a low computational complexity. In addition, the proposed strategy yields a low search delay as well as a low search cost. The performance of the proposed search strategy is superior to the implementation of an optimal single user search on a group of users.

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A method of reducing the wireless cost of tracking mobile users with uncertain parameters is developed in this paper. Such uncertainty arises naturally in wireless networks, since an efficient user tracking is based on a prediction of its future call and mobility parameters. The conventional approach based on dynamic tracking is not reliable in the sense that inaccurate prediction of the user mobility parameters may significantly reduce the tracking efficiency. Unfortunately, such uncertainty is unavoidable for mobile users, especially for bursty mobility pattern.In this study we propose a novel approach, which is efficient yet reliable. The basic idea is to incorporate a distributed scheme with a centralized scheme. The location update process incorporates a topology-independent distance based strategy and a load-sensitive timer. This combination forms a mechanism that bounds from above the total tracking cost. The registration activity is governed by the system, such that it increases at lowly loaded cells and decreases at heavily loaded cells.The expected wireless cost of tracking under the proposed method is significantly reduced, in comparison to the existing methods currently used in cellular networks. Furthermore, as opposed to other tracking methods, the worst case tracking cost is bounded from above and governed by the system. The proposed strategy can be easily implemented, and it does not require a significant computational power from the user.