User mobility modeling and characterization of mobility patterns (original) (raw)
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Impact of mobility models on the cell residence time in WLAN networks
2009 IEEE Sarnoff Symposium, 2009
Several mobility models are available for simulating WLAN, with different impacts on network performance. This work deals with the impact of the assumed mobility model on two key teletraffic variables involved in the planning of the network: the cell residence time (i.e., time connected to an access point) and the handoff rate. These two variables are studied in different scenarios for WLANs designed for pedestrians. For this purpose, discrete event simulations are run with different mobility patterns and number of access points. The time between changes of access point (i.e., handoffs) is studied as a random variable. This research proves the importance of correctly selecting the assumed mobility pattern, as it has a strong impact on the number of handoffs. The probability density function of the cell residence time is also studied as a combination of a distribution that models fast disassociation events (i.e., short ping-pongs between two access points) and a gamma or lognormal distribution, depending on the mobility pattern, which model longer dwells.
Characterizing and modeling user mobility in a cellular data network
Proceedings of the 2nd ACM international workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks - PE-WASUN '05, 2005
The demand for cellular data networks is expected to increase with 3G and beyond technologies accompanied by highbandwidth consumer services, such as wireless video and camera phones. User mobility affects quality of service, and makes capacity planning more difficult. This paper presents an analysis of user mobility patterns based on data traffic traces from a major regional CDMA2000 cellular network. We find low overall mobility in the network, power-law characteristics in user mobility profiles, and weak correlations between call activity and mobility levels for individual users. We also find that users concentrate their activity in a "home cell" with frequent shorter trips to other locations in the network. Based on the empirical findings, we develop and parameterize a model of cellular data user mobility and show its practical use in simulation.
Cell Stay Time Analysis under Random Way Point Mobility Model in WLAN
IEEE Communications Letters, 2000
This letter presents an analytical framework of the Cell Stay Time (CST) in wireless LAN environment. CST is an important parameter that can be used to estimate how long a mobile user will stay in a particular cell and how many cells he will probably visit during his call holding time. CST can be also used to make predictive advanced reservations. A probability density function p.d.f. of the CST is obtained and an analytical expression of its main parameters such as the average and standard deviation values is outlined as a function of the average mobile user speed and cell radius.
Probabilistic model for mobility in cellular network subscriber
In this work, we have studied the behavior and mobility of a cellular network subscriber who belong to a determined class such as (personal employee, student, retired and others) between different areas. Our contribution in this work is a proposition of a mobility model that reproduce in deterministic and probabilistic case, the possible traffic of cellular network subscriber between specified areas with different velocity. Our model incorporate many parameters, such as area size, the number of subscribers, areas types, subscribers types, moving velocity and the direction of users moving. The result obtained, show us that the behavior of mobile station in a cellular network can be approximated to a vehicular traffic model in the deterministic and probabilistic case. 1 aymen.ayari@gmail.com 2
Mobility Management and Performance Statistics in Cellular Communication
IJIRMPS, 2020
This study presents and examines a management model of cellular mobility protocols and the performance of some of its parameters for optimal spectral efficiency of the mobile communication system. Mobility management enables the networks to track the location of mobile nodes. Location management encompasses location registration and call delivery or paging. With the convergence of the internet and wireless mobile communications and with the rapid growth in the number of mobile subscribers, mobility management emerges as one of the most important and challenging problems for wireless mobile communication over the internet. This work is presented on the platform of an analytical framework that can enhance considerably the mobility mechanism in wireless network. Some advance schemes namely, guard channels, and handover queuing are discussed . All these prioritization schemes have a common characteristic reducing the call dropping probability at the expense of increased call blocking probability. The mobility management scheme addressed latency in the service delivery enhancing the guaranteed quality of service (QoS) and an efficient and robust channel capacity.
In cellular networks with a large number of micro-cells, in a blocking environment, the nature of handoff traffic is more realistically represented by general arbitrarily distributed inter-arrival times. Researchers have already shown that for fast moving users or small cell size, the nature of handoff traffic doesn't remain memoryless Poisson type. In case of a network in a 3-D high-rise building, a rectangular micro-cell may be suggested by considering artificial structures such as corridors or lanes, passages within the building and an elevator. We have considered an already described model to estimate the followings. We first estimate the ratio of mean busy call duration to idle duration with mobility under a given network configuration by modeling handoff traffic with a Poisson distribution as well as a General distribution. We further analyse the effects of such modeling of handoff traffic on Engset blocking probability model.
Forecasting the next handoff for users moving with the Random Waypoint mobility model
2013
Users in a cellular network can move while their connections are handed off to different access points. Studies prove that the mobility pattern followed have a strong impact on performance metrics (i.e., handoff (HO) rate, cell residence time). Recently, some key aspects of the Random Waypoint mobility model have been studied in depth, but relating those studies with different cellular layouts has not been reported. Interest in forecasting the cell to which a device may be handed off depending on the movement pattern is twofold. First, it gives insight into properties and statistics of the mobility model. Second, and from a more practical perspective, it is useful to manage resource allocation and reservation strategies in order to smooth the HO process. The goal of this article is to provide an analytical framework for these predictions in a simple layout. Given a node's current location and the timestamp and location of the last waypoint, an approximation for HO during time Δt is derived. The analysis is provided along with numerical examples and simulations for a symmetrical layout and uniform speed distribution. Results shed light on how useful more advanced strategies can be.
Subscriber Mobility Modeling in Wireless Networks
2007
In this paper, a simplified model for user mobility behavior for wireless networks is developed. The model takes into account speed and direction of motion, the two major characteristics of user mobility. A user mobility simulation based on the model is developed, and its results are compared with those in published work. The transient performance metrics of a mobile network are analyzed in terms of trajectory prediction, mean location update rate, and new/handoff call residence time distribution. The proposed mobility model yields results that match very well with those obtained from previously reported complex mobility models.
Mobility modeling in third-generation mobile telecommunications systems
IEEE Personal Communications, 1997
In mobile communications, mobility modeling is involved in several aspects related to signaling and traffic load analysis. In third generation systems, the influence of mobility on the network performance (e.g., handover rate) will be strengthened, mainly due to the huge number of mobile users in conjunction with the small cell size. In particular, the accuracy of mobility models becomes essential for the evaluation of system design alternatives and network implementation cost issues. In this paper, we propose three basic types of mobility models, which are appropriate for the analysis of the full range of mobile communications' design issues. The models provide different levels of detail regarding the user mobility behavior. In particular: (a) the City Area Model traces user motion at an area zone level, (b) the Area Zone Model considers users moving on a street network and (c) the Street Unit Model tracks user motion with an accuracy of a few meters. The validity of the basic models for mobile communications' design aspects is highlighted. Moreover, an "integrated mobility modeling tool", which considers the basic mobility models as components is proposed, aiming at the development of a refined modeling approach. This is achieved by improving the accuracy of the input parameters of each basic model, via the exchange of some specific (mobility related) parameters among the component models. To justify the applicability of the proposed integrated tool for both the analysis of design aspects and network planning, indicative results are presented, derived from simulation-based application examples of the three basic mobility models.