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

Stochastic Geometry Based Analysis of Capacity, Mobility and Energy Efficiency for Dense Heterogeneous Networks

In recent years, the increase in the population of mobile users and the advances in computational capabilities of mobile devices have led to an exponentially increasing traffic load on the wireless networks. This trend is foreseen to continue in the future due to the emerging applications such as cellular Internet of things (IoT) and machine type communications (MTC). Since the spectrum resources are limited, the only promising way to keep pace with the future demand is through aggressive spatial reuse of the available spectrum which can be realized in the networks through dense deployment of small cells. There are many challenges associated with such densely deployed heterogeneous networks (HetNets). The main challenges which are considered in this research work are capacity enhancement, velocity estimation of mobile users, and energy efficiency enhancement. We consider different approaches for capacity enhancement of the network. In the first approach, using stochastic geometry we theoretically analyze time domain inter-cell interference coordination techniques in a two-tier HetNet and optimize the parameters to maximize the capacity of the network. In the second approach, we consider optimization of the locations of aerial bases stations carried by the unmanned aerial vehicles (UAVs) to enhance the capacity of the network for public safety and emergency communications, in case of damaged network infrastructure. In the third approach, we introduce a subsidization scheme for the service providers through which the network capacity can be improved by using regulatory power of the government. Finally, we consider the approach of device-to-device communications and multi-hop transmissions for enhancing the capacity of a network. Velocity estimation of high speed mobile users is important for effective mobility management in densely deployed small cell networks. In this research, we introduce two novel methods for the velocity estimation of mobile users: handover-count based velocity estimation, and sojourn time based velocity estimation. Using the tools from stochastic geometry and estimation theory, we theoretically analyze the accuracy of the two velocity estimation methods through Cramer-Rao lower bounds (CRLBs). With the dense deployment of small cells, energy efficiency becomes crucial for the sustained operation of wireless networks. In this research, we jointly study the energy efficiency and the spectral efficiency in a two-tier HetNet. We optimize the parameters of inter-cell interference coordination technique and study the trade-offs between the energy efficiency and spectral efficiency of the HetNet

Challenges Imposed by User's Mobility in Future HetNet: Offloading and Mobility Management

The users' mobility imposes challenges to mobility management and, the offloading process, which hinder the conventional heterogeneous networks (HetNets) in meeting the huge data traffic requirements of the future. In this thesis, a trio-connectivity (TC), which includes a control-plane (C-plane), a user-plane (U-plane) and an indication-plane (I-plane), is proposed to tackle these challenges. Especially, the I-plane is created as an indicator to help the user equipment (UE) identify and discover the small cells in the system prior to offloading her from the overloaded cells e.g. macro cells, to the cells with abundant resources e.g. small cells. In order to show the advantages of the proposed TC structure, a comparison between the TC and the dual-connectivity (DC) is presented in this thesis, in terms of uplink energy efficiency (ULEE) and energy consumption. Furthermore, the complexity of mobility management is addressed in this thesis as the HetNets will have to handle a large number of UEs and their frequent handoffs due to very dense small-footprint small cells. Considering an accurate mobility framework is essential not only to find the potential offloading to the small cells but also to show the mobility impact on the quality of service (QoS). This thesis presents a framework to model and derive the coverage of small cells, the cell sojourn time and the handoff rate in a multi-tier HetNet by taking into account the overlap coverage among the small cells. The results show the effects of a number of parameters, including the density and the transmit power of the small cells and the power control factor, on the system performance. They also show that the TC can outperform the DC in dense HetNets in terms of energy efficiency and energy consumption

Theoretical analysis of REM-based handover algorithm for heterogeneous networks

© 2013 IEEE. Handover has been a widely studied topic since the beginning of the mobile communications era, but with the advent of another generation, it is worth seeing it with fresh eyes. Data traffic is expected to keep growing as new use cases will coexist under the same umbrella, e.g., vehicle-to-vehicle or massive-machine-type communications. Heterogeneous networks will give way to multi-tiered networks, and mobility management will become challenging once again. Under the current approach, based uniquely on measurements, the number of handovers will soar, so will the signaling. We propose a handover algorithm that employs multidimensional radio-cognitive databases, namely radio environment maps, to predict the best network connection according to the user's trajectory. Radio environment maps have been extensively used in spectrum-sharing scenarios, and recently, some advances in other areas have been supported by them, such as coverage deployment or interference management. We also present a geometric model that translates the 3GPP specifications into geometry and introduce a new framework that can give useful insights into our proposed technique's performance. We validate our framework through Monte Carlo simulations, and the results show that a drastic reduction of at least 10% in the ping-pong handovers can be achieved, thus reducing the signaling needed