Mobility modeling and management for next generation wireless networks

Mobility modeling and management in wireless networks are the set of tasks performed in order to model motion patterns, predict trajectories, get information on mobiles\u27 whereabouts and to make use of this information in handoff, routing, location management, resource allocation and other functions. In the literature, the speed of mobile is often and misleadingly referred to as the level of mobility, such as high or low mobility. This dissertation presents an information theoretic approach to mobility modeling and management, in which mobility is considered as a measure of uncertainty in mobile\u27s trajectory, that is, the mobility is low if the trajectory of a mobile is highly predictable even if the mobile is moving with high speed. On the other hand, the mobility is high if the trajectory of the mobile is highly erratic. Based on this mobility modeling concept, we classify mobiles into predictable and non-predictable mobility classes and optimize network operations for each mobility class. The dynamic mobility classification technique is applied to various mobility related issues of the next generation wireless networks such as location management, location-based services, and energy efficient routing in multihop cellular networks

Enhanced distance-based location management of mobile communication systems using a cell coordinates approach

In managing the locations of mobile users in mobile communication systems, the distance-based strategy has been proven to have better performance than other dynamic strategies, but is difficult to implement. In this paper, a simple approach is introduced to implement the distance-based strategy by using the cell coordinates in calculating the physical distance traveled. This approach has the advantages of being independent of the size, shape, and distribution of cells, as well as catering for the direction of movement in addition to the speed of each mobile terminal. An enhanced distance-based location management strategy is proposed to dynamically adjust the size and shape of location area for each individual mobile terminal according to the current speed and direction of movement. It can reduce the location management signaling traffic of the distance-based strategy by half when mobile terminals have predictable directions of movement. Three types of location updating schemes are discussed, namely, Circular Location Area, Optimal Location Area, and Elliptic Location Area. Paging schemes using searching techniques such as expanding distance search based on the last reported location and based on the predicted location, and expanding direction search are also explored to further reduce paging signal traffic by partitioning location areas into paging areas.published_or_final_versio

A new splitting-based displacement prediction approach for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Several location prediction models have been proposed to enhance and increase the relevance of the information retrieved by users of mobile information systems, but none of them studied the relationship between accuracy rate of prediction and the performance of the model in terms of consuming resources and constraints of mobile devices. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. One such technique is the Prediction Location Model (PLM), which deals with inner cell structure. The PLM technique suffers from memory usage and poor accuracy. The main goal of this paper is to propose a new path prediction technique for Location-Based Services. The new approach is competitive and more efficient compared to PLM regarding measurements such as accuracy rate of location prediction and memory usage

Location Management Cost Reduction Using Adaptive Velocity-movement Based Scheme

Wireless personal communication networks (PCNs) consist of a fixed wireless network and a large number of mobile terminals. These terminals are free to travel within the PC coverage area without service interruption. Each terminal periodically reports its location to the network by a process called location update (or registration). When a call arrives for a particular mobile terminal, the network will determine the exact location of the destination terminal by a process called terminal paging. One major problem that arises in this scenario is the cost associated with paging and registration. Several papers in the literature attempt to reduce the cost by devising new schemes for paging and registration. One of the many interesting schemes was presented by Wan and Lin (1998) that considers a dynamic paging scheme based on the semi-real time velocity information of an individual mobile user, which allows a more accurate prediction of the user location when a call arrives. In this paper, we modified the scheme presented by Wan and Lin by creating an adaptive velocity timer that changes according to the speed of the mobile and applies the same analysis to the movement-based scheme. The investigation shows that the proposed approach of Wan and Lin has better results than what was reported therein and our new approach helps reduce the total cost drastically compared to the original scheme. Results also show that the movement threshold and the adaptive velocity time unit, when they are adaptive, provide significant savings of cost under different cell sizes and velocities in high and low mobility systems

User-oriented mobility management in cellular wireless networks

2020 Spring.Includes bibliographical references.Mobility Management (MM) in wireless mobile networks is a vital process to keep an individual User Equipment (UE) connected while moving within the network coverage area—this is required to keep the network informed about the UE's mobility (i.e., location changes). The network must identify the exact serving cell of a specific UE for the purpose of data-packet delivery. The two MM procedures that are necessary to localize a specific UE and deliver data packets to that UE are known as Tracking Area Update (TAU) and Paging, which are burdensome not only to the network resources but also UE's battery—the UE and network always initiate the TAU and Paging, respectively. These two procedures are used in current Long Term Evolution (LTE) and its next generation (5G) networks despite the drawback that it consumes bandwidth and energy. Because of potentially very high-volume traffic and increasing density of high-mobility UEs, the TAU/Paging procedure incurs significant costs in terms of the signaling overhead and the power consumption in the battery-limited UE. This problem will become even worse in 5G, which is expected to accommodate exceptional services, such as supporting mission-critical systems (close-to-zero latency) and extending battery lifetime (10 times longer). This dissertation examines and discusses a variety of solution schemes for both the TAU and Paging, emphasizing a new key design to accommodate 5G use cases. However, ongoing efforts are still developing new schemes to provide seamless connections to the ever-increasing density of high-mobility UEs. In this context and toward achieving 5G use cases, we propose a novel solution to solve the MM issues, named gNB-based UE Mobility Tracking (gNB-based UeMT). This solution has four features aligned with achieving 5G goals. First, the mobile UE will no longer trigger the TAU to report their location changes, giving much more power savings with no signaling overhead. Instead, second, the network elements, gNBs, take over the responsibility of Tracking and Locating these UE, giving always-known UE locations. Third, our Paging procedure is markedly improved over the conventional one, providing very fast UE reachability with no Paging messages being sent simultaneously. Fourth, our solution guarantees lightweight signaling overhead with very low Paging delay; our simulation studies show that it achieves about 92% reduction in the corresponding signaling overhead. To realize these four features, this solution adds no implementation complexity. Instead, it exploits the already existing LTE/5G communication protocols, functions, and measurement reports. Our gNB-based UeMT solution by design has the potential to deal with mission-critical applications. In this context, we introduce a new approach for mission-critical and public-safety communications. Our approach aims at emergency situations (e.g., natural disasters) in which the mobile wireless network becomes dysfunctional, partially or completely. Specifically, this approach is intended to provide swift network recovery for Search-and-Rescue Operations (SAROs) to search for survivors after large-scale disasters, which we call UE-based SAROs. These SAROs are based on the fact that increasingly almost everyone carries wireless mobile devices (UEs), which serve as human-based wireless sensors on the ground. Our UE-based SAROs are aimed at accounting for limited UE battery power while providing critical information to first responders, as follows: 1) generate immediate crisis maps for the disaster-impacted areas, 2) provide vital information about where the majority of survivors are clustered/crowded, and 3) prioritize the impacted areas to identify regions that urgently need communication coverage. UE-based SAROs offer first responders a vital tool to prioritize and manage SAROs efficiently and effectively in a timely manner