https://titania.ctie.monash.edu/papers/vhd-survey-comp-networks-2010.pdf

A survey of vertical handover decision algorithms in Fourth Generation heterogeneous wireless networks

Wireless networks are passing through a transition phase for the past few years now and this transition is giving a way towards the convergence of all IP-based networks to form the Next Generation Networks (NGNs). With the proliferation of these networks in daily life, users' needs are also increasing and service operators are offering different services to satisfy their customers for a better grade of service and an elevated quality of experience (QoE). However, a single operator cannot fulfill the huge demands of the users especially, if a user is nomadic. In nomadism, a user traverses number of available networks that might contain cellular or wireless data networks, usually known as heterogeneous wireless networks. These networks offer various services from email to live video streaming depending upon their capacity and nature. During this traversing procedure, a user switches among different networks to satisfy his/her needs in terms of quality of service. This process is commonly known as a vertical handover or handoff (VHO) due to the involvement of heterogeneous wireless networks in it. An extensive work has been carried out in this field in order to fulfill user demands for better QoS and QoE. In this paper, we give a detailed state-of-the-art of these existing vertical handover decision mechanisms that aim at providing ubiquitous connectivity to the mobile users. We have categorized these vertical handover measurement and decision schemes on the basis of their employed techniques and parameters. Also, we present a comprehensive summary of their advantages and drawbacks. This paper gives its readers an overview of the active research initiatives in the area of handover decision making process in heterogeneous wireless networks and identifies the challenges behind the seamless services provisioning during mobility.

Enabling Vertical Handover Decisions in Heterogeneous Wireless Networks: A State-of-the-Art and A Classification

To reduce the number of unnecessary handover in hierarchical macro/femto-cell networks, it is necessary to avoid macro -> femto cell handovers of temporary femtocell visitors who stay in the femtocell for a relatively short time. In this paper, we propose a smart handover decision algorithm exploiting future mobility pattern prediction scheme to prevent macro -> femto cell handovers of such temporary femtocell visitors. Our simulation result shows that the proposed algorithm effectively reduces the number of unnecessary handovers.

A Smart Handover Decision Algorithm Using Location Prediction for Hierarchical Macro/Femto-Cell Networks

계층화된 Macro/Femto 셀 네트워크에서의 단말의 미래 위치 예측 기법을 이용한 향상된 핸드오버 결정 알고리즘 = A smart handover decision algorithm using location prediction for hierarchical macro/femto-cell networks

The authors focus on the network selection problem in heterogeneous wireless networks. Many traditional approaches select the best network according to quality of service (QoS)-related criteria, which neglects diverse user demands. The authors aim to select networks maximizing the quality of experience (QoE) of users. When the availability and dynamics of network state information (NSI) are considered, most of the existing approaches cannot make effective selection decisions since they are vulnerable to the uncertainty in NSI. To address this issue, the authors introduce the idea of online learning for network selection. In this paper, the authors formulate the network selection problem as a continuous-time multiarmed bandit (CT-MAB) problem. A traffic-aware online network selection (ONES) algorithm is designed to match typical traffic types of users with respective optimal networks in terms of QoE. Moreover, the authors found that the correlation among multiple traffic network selections can be exploited to improve the learning capability. This motivates the authors to propose another two more efficient algorithms: the decoupled ONES (D-ONES) algorithm and the virtual multiplexing ONES (VM-ONES) algorithm. Simulation results demonstrate that the authors ONES algorithms attain around 10% gain in QoE reward rate over nonlearning-based algorithms and learning-based algorithms without QoE considerations.

Traffic-Aware Online Network Selection in Heterogeneous Wireless Networks

We propose a handover decision method based on the prediction of traveling distance within an IEEE 802.11 wireless local area network (WLAN) cell. The method uses two thresholds which are calculated by the mobile terminal (MT) as it enters the WLAN cell. The predicted traveling distance is compared against these thresholds to make a handover decision in order to minimize the probability of handover failures or unnecessary handovers from a cellular network to a WLAN. Our analysis shows that the proposed method successfully keeps the number of failed or unnecessary handovers low.

https://titania.ctie.monash.edu.au/papers/iris-traveling-distance-2008.pdf

N. Mani

Papers

A Traveling Distance Prediction Based Method to Minimize Unnecessary Handovers from Cellular Networks to WLANs