69 research outputs found

    Mitigation of Redundant Handovers to Femtocells by Estimation of throughput Gain

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    Project Final Report – FREEDOM ICT-248891

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    This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.Preprin

    Mobility Management for Small Cells in LTE-A Networks

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    Katedra telekomunikaÄŤnĂ­ technik

    A New Approach for the Minimization of Packet Losses in LTE Networks

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    This research work presents a new approach for minimization of packet losses in Long Term Evolution (LTE) networks. A prominent design feature for vertical handover decision algorithm is to ensure seamless handover process between different wireless access technologies without compromising the Quality of Service (QoS) and Quality of Experience (QoE) of the users. There are scenarios in handover schemes, where due to poor handover process, frequent handover occur leading to packet losses and subsequent dissatisfaction of the users. A handover decision algorithm that incorporates the user’s changing speed into a proximity model prediction technique (PMPT) in order to minimize packet losses during handover process between macrocell and femtocell networks is presented in this paper. The developed algorithm is designed to make appropriate prediction based on the established communication link to either the macrocell or femtocell network as the User Vehicle (UV) speed changes. Results obtained using MATLAB R2015b shows that the developed vertical handover algorithm (DVHA) attained a 77.07% reduction in packet loss ratio over the existing vertical handover algorithm (EVHA)

    Estimation of Signal Level Evolution for Handover in Networks with Femtocells

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    The deployment of small cells is one of the solutions used by the operators in order to improve their coverage and the quality of service (QoS) offered in urban scenarios. However, an increase in the amount of available cell could represent a problem for the operators due to a higher number of performed handovers. Moreover, if we take into account that the density of femtocells deployed and the number of users in the same scenario could be high, the problem of performing handover becomes even more significant. An algorithm to decrease the number of performed handovers in a scenario with femtocells deployed densely is studied in this thesis. The proposed algorithm estimates the future signal level, which the user would receive if it performs the handover to the target cell. This estimate is exploited to evaluate if handover is going to be beneficial in terms of throughput or not. The performance is compared with the conventional handover technique and with selected competitive algorithms. The results show that the proposed algorithm decreases the number of performed handovers and, in addition, it maintains an acceptable level of SINR even for the scenarios with high density of femtocells.Gomar Llario, J. (2015). Estimation of Signal Level Evolution for Handover in Networks with Femtocells. http://hdl.handle.net/10251/52508.Archivo delegad

    Theoretical analysis of REM-based handover algorithm for heterogeneous networks

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    © 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

    Control and data channel resource allocation in OFDMA heterogeneous networks

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    This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macro cells and small cells sharing the same frequency band. Dense deployment of small cells overlaid by a macro layer is considered to be one of the most promising solutions for providing hotspot coverage in future 5G networks. The focus is to devise an optimised policy for small cells’ access to the shared spectrum, in terms of their transmissions, in order to keep small cell served users sum data rate at high levels while ensuring that certain level of quality of service (QoS) for the macro cell users in the vicinity of small cells is provided. Both data and control channel constraints are considered, to ensure that not only the macro cell users’ data rate demands are met, but also a certain level of Bit Error Rate (BER) is ensured for the control channel information. Control channel reliability is especially important as it holds key information to successfully decode the data channel. The problem is addressed by our proposed linear binary integer programming heuristic algorithm which maximises the small cells utility while ensuring the macro users imposed constraints. To further reduce the computational complexity, we propose a progressive interference aware low complexity heuristic solution. Discussion is also presented for the implementation possibility of our proposed algorithms in a practical network. The performance of both the proposed algorithms is compared with the conventional Reuse-1 scheme under different fading conditions and small cell loads. Results show a negligible drop in small cell performance for our proposed schemes, as a trade-off for ensuring all macro users data rate demands, while Reuse-1 scheme can even lead up to 40 % outage when control region of the small cells in heavily loaded
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