290 research outputs found

    On the Minimization of Handover Decision Instability in Wireless Local Area Networks

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    This paper addresses handover decision instability which impacts negatively on both user perception and network performances. To this aim, a new technique called The HandOver Decision STAbility Technique (HODSTAT) is proposed for horizontal handover in Wireless Local Area Networks (WLAN) based on IEEE 802.11standard. HODSTAT is based on a hysteresis margin analysis that, combined with a utilitybased function, evaluates the need for the handover and determines if the handover is needed or avoided. Indeed, if a Mobile Terminal (MT) only transiently hands over to a better network, the gain from using this new network may be diminished by the handover overhead and short usage duration. The approach that we adopt throughout this article aims at reducing the minimum handover occurrence that leads to the interruption of network connectivity (this is due to the nature of handover in WLAN which is a break before make which causes additional delay and packet loss). To this end, MT rather performs a handover only if the connectivity of the current network is threatened or if the performance of a neighboring network is really better comparing the current one with a hysteresis margin. This hysteresis should make a tradeoff between handover occurrence and the necessity to change the current network of attachment. Our extensive simulation results show that our proposed algorithm outperforms other decision stability approaches for handover decision algorithm.Comment: 13 Pages, IJWM

    A Comparative study on Handoff Algorithms for GSM and CDMA Cellular Networks

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    The GSM, CDMA cellular systems are most trendy 2G and 3G digital cellular telecommunications systems, which is widely used throughout the world. These systems have many advantages such as high security, higher quality of call transmission over the long distances, low transmitted power, and enhanced capacity with more efficient utilization of the frequency spectrum. With these advantages these cellular systems have attracted more subscribers with more attention in the field of mobile communications. One of the most attractive features of cellular system is handoff which is a continuation of an active call when the mobile is moving from one cell to another without disconnecting the call. Usually, continuous service is achieved by efficiently designed handoff algorithms. So, efficient handoff algorithms are necessary for enhancing the capacity and QoS of cellular system. In this paper, the handoff analysis for GSM, CDMA cellular networks are done under various propagation models. Various handoff algorithms of GSM are described and also a novel received signal strength (RSS) based GSM handoff algorithm with adaptive hysteresis is analyzed. CDMA Soft handoff algorithm is analyzed and effective soft handoff parameters are estimated for better performance. The Comparison of handoff algorithms is studied based on results

    Mitigation of Redundant Handovers to Femtocells by Estimation of throughput Gain

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    A Vertical Handover Algorithm in Integrated Macrocell Femtocell Networks

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    The explosion in wireless telecommunication technologies has lead to a huge increase in the number of mobile users. The greater dependency on the mobile devices has raised the user’s expectations to always remain best connected. In the process, the user is always desiring good signal strength even at certain black spots and indoors. Moreover, the exponential growth of the number of mobile devices has overloaded macrocells. Femtocells have emerged out as a good promising solution for complete coverage indoors and for offloading macrocell. Therefore, a new handover strategy between femtocells and macrocell is proposed in this paper. The proposed handover algorithm is mainly based on calculating equivalent received signal strength along with dynamic margin for performing handover. The simulation results of proposed algorithm are compared with the traditional algorithm. The proposed strategy shows improvement in two major performance parameters namely reduction in unnecessary handovers and Packet Loss Ratio. The quantitative analysis further shows 55.27% and 23.03% reduction in packet loss ratio and 61.85% and 36.78% reduction in unnecessary handovers at a speed of 120kmph and 30kmph respectively. Moreover, the proposed algorithm proves to be an efficient solution for both slow and fast moving vehicles

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

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    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

    A Proposed Policy-Based Management Architecture for Wireless Clients Operating in a Heterogeneous Mobile Environment

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    The objective of this paper is to provide a managed always best connected service to mobile entities over underlying heterogeneous wireless and mobile platforms while maintaining negotiated security and quality of service (QoS). This paper proposes a new model and its architecture which is based upon Policy-based Management but provides a new framework based on layered-approach for the centralised management of mobile clients. In particular, we propose and implement a new model of a policy-managed mobile client and its architecture to support seamless handoff across multiple access networks. The proposed mobile client supports multi-domain authentication, authorisation and security based on user profiles as well as the ability to negotiate management services over interconnected heterogeneous mobile platforms. We have also proposed a new handoff initiation algorithm to select an optimum time to handoff. This algorithm combines metrics in a novel way using standard deviations without resorting to other computationally intensive methods. Finally, this paper describes a proof-of-concept implementation based upon Microsoft Windows presenting a performance analysis to validate our architectural approach

    Performance Comparison of ANN Training Algorithms for Hysteresis Determination in LTE networks

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    Long-Term Evolution (LTE) network is an improved standard for mobile telecommunication system developed by the 3rd Generation Partnership Project (3GPP) requires an efficient handover framework which would reduce hysteresis and improve quality of service (QoS) of subscribers by maximizing scarce radio resources. This paper compares the performance of two ANN prediction algorithms (Levenberg- Marquadt and Bayesian regularization) based on received signal strength (RSS) and the hysteresis margin parameters for neuro-adaptive hysteresis margin reduction algorithm. The Bayesian regularization algorithm had a lower mean error when compared with the Levenberg-Marquadt (LM) prediction algorithm and as such a better option for neuroadaptive hysteresis margin reduction algorithm

    Optimal and practical handover decision algorithms in heteregeneous marco-femto cellular networks

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    Driven by the smart tablet/phone revolution and the proliferation of bandwidth hungry applications such as cloud computing and streaming video, the demand for high data rate wireless communication is increasing tremendously. In order to meet the increasing demand from subscribers, wireless operators are in the process of augmenting their macrocell network with supplemental infrastructure such as microcells, distributed antennas and relays. An alternative with lower upfront costs is to improve indoor coverage and capacity by using end-consumer installed femtocells. A femtocell is a low power, short range (up to 100 meters coverage radius) cellular wireless access point (AP), functioning in service provider owned licensed spectrum. Due to the proximity of end users to the femtocell access points, APs are able to provide higher end-user QoE and better spatial reuse of limited spectrum. Femtocells are useful in offloading the macro-cellular network as well as reducing the operating and capital expenditure costs for operators. Femtocells coexist with legacy cellular networks consisting of macrocells. In this emerging combined architecture, large number of Femtocell Application Point (FAPs) is randomly deployed in the coverage area of macro BSs. However, several problems related to MM (mobility management) and RM (resource management) in this combined architecture still remain to be solved. The ad hoc deployment of FAPs and asymmetric radio communication and call processing capabilities between macrofemto networks are the primary causes of these problems. Uncoordinated deployment of FAPs providing indoor oriented wireless access service within the macro coverage may cause severe interference problems that need to be mitigated and handled by RM/MM schemes. The MM decisions should take into account the resource constraints and UE mobility in order to prevent unnecessary or undesirable handovers towards femtocells. Ignoring these factors in MM decisions may lead to low customer satisfaction due to mismanagement of handover events in the combined macro-femto network, delayed signaling traffic and unsatisfactory call/connection quality. In order to address all of the aforementioned issues, the handover decision problem in combined femto-macro networks has been formulated as a multi-objective non-linear optimization problem. Since there are no known analytical solution to this problem, an MDP (Markov Decision Process) based heuristic has been proposed as a practical and optimal HO (handover) decision making scheme. This heuristic has been updated and improved in an iterative manner and has also been supported by a dynamic SON (Self Organizing Networks) algorithms that is based on heuristic's components. The performance results show that the final version of MDP based heuristic has signi cantly superior performance in terms offloading the macro network, minimizing the undesirable network events (e.g. outage and admission rejection) when compared to state-of-art handover algorithms
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