Client-based and Cross-layer Optimized Flow Mobility for Android Devices in Heterogeneous Femtocell/Wi-Fi Networks*

AbstractThe number of subscribers accessing Internet resources from mobile and wireless devices has been increasing continually since i-mode, the first mobile Internet service launched in 1999. The handling and support of dramatic growth of mobile data traffic create serious challenges for the network operators. Due to the spreading of WLAN networks and the proliferation of multi-access devices, offloading from 3G to Wi-Fi seems to be a promising step towards the solution. To solve the bandwidth limitation and coverage issues in 3G/4G environments, femtocells became key players. These facts motivate the design and development of femtocell/Wi-Fi offloading schemes. Aiming to support advanced offloading in heterogeneous networks, in this paper we propose a client-based, cross-layer optimized flow mobility architecture for Android devices in femtocell/Wi-Fi access environments. The paper presents the design, implementation and evaluation details of the aforementioned mechanisms

Mobile Data Offloading the Growing Need with Its Solutions and Challenges

From the last few years, the popularity of video, social media and Internet gaming across a range of new devices like smartphones and tablets has created a surge of data traffic over cellular networks. Device to device connectivity will give rise to a new universe of applications that will further create stress on network capacity [3]. In the next three years alone, it is accepted that data traffic will grow towards tenfold creating a tremendous capacity crunch for operators. While data revenues are expected to only double during this period, which will create a huge gap. As a result, different innovative solutions have emerged to man age data traffic. Some of the key technologies include Wi-Fi, LTE Small Cell and Relay, femtocells, DTN-based Network, and IP flow mobility. Therefore, telecom operators need to constantly review their implement traffic offloading mechanisms that will help them manage their network load and capacity mo re efficiently. This paper describes various data offload strategies and considers the challenges and benefits associated with each of them. This paper aims to provide a survey of mobile data offloading technologies including insights from the business per spective as well

Handover Management in Highly Dense Femtocellular Networks

For dense femtocells, intelligent integrated femtocell/macrocell network architecture, a neighbor cell list with a minimum number of femtocells, effective call admission control (CAC), and handover processes with proper signaling are the open research issues. An appropriate traffic model for the integrated femtocell/macrocell network is also not yet developed. In this paper, we present the major issue of mobility management for the integrated femtocell/macrocell network. We propose a novel algorithm to create a neighbor cell list with a minimum, but appropriate, number of cells for handover. We also propose detailed handover procedures and a novel traffic model for the integrated femtocell/macrocell network. The proposed CAC effectively handles various calls. The numerical and simulation results show the importance of the integrated femtocell/macrocell network and the performance improvement of the proposed schemes. Our proposed schemes for dense femtocells will be very effective for those in research and industry to implement

Green Networking in Cellular HetNets: A Unified Radio Resource Management Framework with Base Station ON/OFF Switching

In this paper, the problem of energy efficiency in cellular heterogeneous networks (HetNets) is investigated using radio resource and power management combined with the base station (BS) ON/OFF switching. The objective is to minimize the total power consumption of the network while satisfying the quality of service (QoS) requirements of each connected user. We consider the case of co-existing macrocell BS, small cell BSs, and private femtocell access points (FAPs). Three different network scenarios are investigated, depending on the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs, and HetNets with semi-closed FAPs. A unified framework is proposed to simultaneously allocate spectrum resources to users in an energy efficient manner and switch off redundant small cell BSs. The high complexity dual decomposition technique is employed to achieve optimal solutions for the problem. A low complexity iterative algorithm is also proposed and its performances are compared to those of the optimal technique. The particularly interesting case of semi-closed FAPs, in which the FAPs accept to serve external users, achieves the highest energy efficiency due to increased degrees of freedom. In this paper, a cooperation scheme between FAPs and mobile operator is also investigated. The incentives for FAPs, e.g., renewable energy sharing and roaming prices, enabling cooperation are discussed to be considered as a useful guideline for inter-operator agreements.Comment: 15 pages, 9 Figures, IEEE Transactions on Vehicular Technology 201

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Self-organising comprehensive handover strategy for multi-tier LTE-advanced heterogeneous networks

Long term evolution (LTE)-advanced was introduced as real fourth generation (4G) with its new features and additional functions, satisfying the growing demands of quality and network coverage for the network operators' subscribers. The term muti-tier has also been recently used with respect to the heterogeneity of the network by applying the various subnetwork cooperative systems and functionalities with self-organising capabilities. Using indoor short-range low-power cellular base stations, for example, femtocells, in cooperation with existing long-range macrocells are considered as the key technical challenge of this multi-tier configuration. Furthermore, shortage of network spectrum is a major concern for network operators which forces them to spend additional attentions to overcome the degradation in performance and quality of services in 4G HetNets. This study investigates handover between the different layers of a heterogeneous LTE-advanced system, as a critical attribute to plan the best way of interactive coordination within the network for the proposed HetNet. The proposed comprehensive handover algorithm takes multiple factors in both handover sensing and decision stages, based on signal power reception, resource availability and handover optimisation, as well as prioritisation among macro and femto stations, to obtain maximum signal quality while avoiding unnecessary handovers