1,229 research outputs found

    Novel group handover mechanism for cooperative and coordinated mobile femtocells technology in railway environment

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    Recently, the Mobile Femto (MF) Technology has been debated in many research papers to be a promising solution that will dominate future networks. This small cell technology plays a major role in supporting and maintaining network connectivity, enhancing the communication service as well as user experience for passengers in High-Speed Trains (HSTs) environments. Within the railway environment, there are many MF Technologies placed on HSTs to enhance the train passengers’ internet experience. Those users are more affected by the high penetration loss, path loss, dropped signals, and the unnecessary number of Handovers (HOs). Therefore, it is more appropriate to serve those mobile users by the in-train femtocell technology than being connected to the outside Access Points (APs) or Base Stations (BSs). Hence, having a series of MFs (called Cooperative and Coordinated MFs -CCMF) installed inside the train carriages has been seen to be a promising solution for train environments and future networks. The CCMF Technologies establish Backhaul (BH) links with the serving mother BS (DeNB). However, one of the main drawbacks in such an environment is the frequent and unnecessary number of HO procedures for the MFs and train passengers. Thus, this paper proposes an efficient Group HO mechanism that will improve signal connection and mitigate the impact of a signal outage when train carriages move from one serving cell to another. Unlike most work that uses Fixed Femtocell (FF) architecture, this work uses MF architecture. The achieved results via Matlab simulator show that the proposed HO scheme has achieved less outage probability of 0.055 when the distance between the MF and mobile users is less than 10 m compared to the signal outage probability of the conventional HO scheme. More results have shown that the dropping calls probability has been reduced when mobile users are connected to the MF compared to the direct transmission from the eNB. That is in turn has have improved the call duration of mobile UEs and reduced the dropping calls probability for mobile users who are connected to the MF compared to eNB direct connection UEs

    Performance analysis of massive multiple input multiple output for high speed railway

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    This paper analytically reviews the performance of massive multiple input multiple output (MIMO) system for communication in highly mobility scenarios like high speed Railways. As popularity of high speed train increasing day by day, high data rate wireless communication system for high speed train is extremely required. 5G wireless communication systems must be designed to meet the requirement of high speed broadband services at speed of around 500 km/h, which is the expected speed achievable by HSR systems, at a data rate of 180 Mbps or higher. Significant challenges of high mobility communications are fast time-varying fading, channel estimation errors, doppler diversity, carrier frequency offset, inter carrier interference, high penetration loss and fast and frequent handovers. Therefore, crucial requirement to design high mobility communication channel models or systems prevails. Recently, massive MIMO techniques have been proposed to significantly improve the performance of wireless networks for upcoming 5G technology. Massive MIMO provide high throughput and high energy efficiency in wireless communication channel. In this paper, key findings, challenges and requirements to provide high speed wireless communication onboard the high speed train is pointed out after thorough literature review. In last, future research scope to bridge the research gap by designing efficient channel model by using massive MIMO and other optimization method is mentioned

    Communication Technologies Support to Railway Infrastructure and Operations

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    Algoritmos de transferência de redes LTE em meios de transporte massivo

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    Handover in LTE occurs when a device moves from the cell coverage serving it towards another; a process where the user established session must not be interrupted due to this cell change. Handovers in LTE are classified as hard ones, since the link with the serving cell is interrupted before establishing the new link with the target cell. This entails a larger failure risk and, consequently, a potential deterioration in the quality of service. This article presents a review of the handover algorithms in LTE, focusing on the ones oriented to massive means of transport. We show how the new algorithms offer a larger success in handovers, increasing the networkdata rate. This indicates that factors such as speed, position, and direction should be included in the algorithms to improve the handover in means of transport. We also present the algorithms focused on mobile relays such as an important study field for future research works.El traspaso en LTE se presenta cuando un equipo pasa de la cobertura de una celda a la de otra, un proceso en el que se debe asegurar que el usuario no vea interrumpida su sesión, como efecto de ese cambio de celda. Los traspasos en LTE son del tipo duro, en ellos, el enlace con la celda servidora se interrumpe antes de establecer el nuevo enlace con la celda destino, lo que conlleva a un mayor riesgo de falla y con ello a un probable deterioro de la calidad del servicio al usuario. Este artículo revisa algoritmos de traspaso LTE, enfocándose en aquellos orientados a medios de trasporte masivo. Muestra cómo los nuevos algoritmos ofrecen una tasa mayor de traspasos exitosos y con ello una mejor tasa de transferencia de datos; evidencia que factores como la velocidad, la posición y la dirección deben ser incluidos en los algoritmos dirigidos a mejorar el traspaso en medios de transporte; y presenta a los algoritmos enfocados en relays móviles, como un importante campo de estudio para futuras investigaciones.A transferência em LTE ocorre quando um dispositivo passa da cobertura de uma célula para outra, um processo no qual deve ser assegurado que o usuário não veja sua sessão interrompida, como resultado dessa mudança de célula. As transferências em LTE são do tipo duro, nelas, o link com a célula do servidor é interrompido antes de se estabelecer o novo link com a célula alvo, o que leva a um maior risco de falha e, portanto, a uma provável deterioração da qualidade do serviço ao usuário. Este artigo revisa os algoritmos de transferência LTE, com foco naqueles orientados a meios de transporte massivo. Mostra como os novos algoritmos oferecem uma taxa maior de transferências bem-sucedidas e, com isso, uma melhor taxa de transferência de dados; evidencia de que fatores como a velocidade, a posição e a direção devem ser incluídos nos algoritmos que visam melhorar a transferência nos meios de transporte; e apresenta os algoritmos focados em relés móveis, como um importante campo de estudo para futuras pesquisas

    A Moving Direction and Historical Information Assisted Fast Handover in LTE-A

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    Handover is one of the critical features in mobility management of Long Term Evolution Advanced (LTE-A) wireless systems. It allows the User Equipment (UE) to roam between LTE-A wireless networks. LTE-A is purely on hard handover, which may cause loss data if the handover is not fast. In this paper, an advanced technique proposed which combined between the current UE moving direction and its history information. Our proposed tracks the UE positions to discover its direction. When the UE is being near to handover area the UE starts searching in its history to return back the target cell. If the UE trajectory does not exist in its history then the UE and its serving cell start searching for target cell through using cosine function in order to select target cell.  Our proposed technique is expected to increase the throughput, reduce the packet delay and loss, and reduce the frequent handovers

    Network selection mechanism for telecardiology application in high speed environment

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    The existing network selection schemes biased either to cost or Quality of Service (QoS) are not efficient enough for telecardiology application in high traveling speed environment. Selection of the candidate network that is fulfilling the telecardiology service requirements as well as user preference is a challenging issue. This is because the preference of telecardiology user might change based on the patient health condition. This research proposed a novel Telecardiology-based Handover Decision Making (THODM) mechanism that consists of three closely integrated algorithms: Adaptive Service Adjustment (ASA), Dwelling Time Prediction (DTP) and Patient Health Condition-based Network Evaluation (PHCNE). The ASA algorithm guarantees the quality of telecardiology service when none of the available networks fulfils the service requirements. The DTP algorithm minimizes the probability of handover failure and unnecessary handover to Wireless Local Area Network (WLAN), while optimizing the connection time with WLAN in high traveling speed environment. The PHCNE algorithm evaluates the quality of available networks and selects the best network based on the telecardiology services requirement and the patient health condition. Simulation results show that the proposed THODM mechanism reduced the number of handover failures and unnecessary handovers up to 80.0% and 97.7%, respectively, compared with existing works. The cost of THODM mechanism is 20% and 85.3% lower than the Speed Threshold-based Handover (STHO) and Bandwidth-based Handover (BWHO) schemes, respectively. In terms of throughput, the proposed scheme is up to 75% higher than the STHO scheme and 370% greater than the BWHO scheme. For telecardiology application in high traveling speed environment, the proposed THODM mechanism has better performance than the existing network selection schemes

    Final report on the evaluation of RRM/CRRM algorithms

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    Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin
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