Network-Based UE Mobility Estimation in Mobile Networks

International audienceThe coexistence of small cells and macro cells is a key feature of 4G and future networks. This heterogeneity, together with the increased mobility of user devices can generate a high handover frequency that could lead to unreasonably high call drop probability or poor user experience. By performing smart mobility management, the network can pro-actively adapt to the user and guarantee seamless and smooth cell transitions. In this work, we introduce an algorithm that takes as input sounding reference signal (SRS) measurements available at the base station (eNodeB in 4G systems) to estimate with a low computational requirement the mobility level of the user and with no modification at the user device/equipment (UE) side. The performance of the algorithm is showcased using realistic data and mobility traces. Results show that the classification of UE speed to three mobility classes can be achieved with accuracy of 87% for low mobility, 93% for medium mobility, and 94% for high mobility, respectively

A Study of Sojourn Time for Indoor LiFi Cellular Networks

Sojourn time is an important parameter in the analysis and design of mobile cellular networks. It shows the expected time that a user equipment (UE) remains connected to the serving access point (AP) while moving in the network, i.e. stays within one cell. Therefore, an accurate estimation of the sojourn time is an essential element for mobility management. In this study, an analysis of the sojourn time for indoor light-fidelity (LiFi) cellular networks is presented based on the random waypoint (RWP) mobility model. It is initially assumed that the UE is oriented vertically upward and closed-form analytical expressions are derived. Monte-Carlo simulations are also provided to validate the analytical derivations and to gain more insight into the performance with different orientations. It is shown that the sojourn time mainly varies depending on the speed of the user. However, other factors such as the device orientation and the coverage area of cells also play a role in determining the sojourn time. The results offer several insights and design guidelines in consideration of this parameter for indoor LiFi networks

zCap: a zero configuration adaptive paging and mobility management mechanism

Today, cellular networks rely on fixed collections of cells (tracking areas) for user equipment localisation. Locating users within these areas involves broadcast search (paging), which consumes radio bandwidth but reduces the user equipment signalling required for mobility management. Tracking areas are today manually configured, hard to adapt to local mobility and influence the load on several key resources in the network. We propose a decentralised and self-adaptive approach to mobility management based on a probabilistic model of local mobility. By estimating the parameters of this model from observations of user mobility collected online, we obtain a dynamic model from which we construct local neighbourhoods of cells where we are most likely to locate user equipment. We propose to replace the static tracking areas of current systems with neighbourhoods local to each cell. The model is also used to derive a multi-phase paging scheme, where the division of neighbourhood cells into consecutive phases balances response times and paging cost. The complete mechanism requires no manual tracking area configuration and performs localisation efficiently in terms of signalling and response times. Detailed simulations show that significant potential gains in localisation effi- ciency are possible while eliminating manual configuration of mobility management parameters. Variants of the proposal can be implemented within current (LTE) standards

Advanced Positioning and Location based services in 4G Mobile-IP Radio Access Networks

2004 IEEE 15TH IEEE International Symposium on personal, indoor and mobile radio communications (PIMRC 2004), Barcelona, Spain, 5-8 september 2004.This paper proposes an evolved architecture from 3G networks to provide basic and advanced positioning methods for location based services in mobile IPv6-based radio access networks. We start analyzing current status of location-based services (i.e. LBS or LCS) and architectures in 3G networks as well as state-of-the-art research on LBS and mobile Internet. Next we set the requirements the solution should fulfill. We continue proposing the evolved architecture for support of basic and advanced positioning methods, using MIPv6 and HMIPv6 as mobility scenario for the mobile IPv6 based RAN, describing element's functions and changes from current approaches as well as description of the dynamic behavior. We complete the proposal with a bandwidth analysis of the signaling, identifying issues when planning implementation of LCS services in the network