Regressive Prediction Approach to Vertical Handover in Fourth Generation Wireless Networks

The over increasing demand for deployment of wireless access networks has made wireless mobile devices to face so many challenges in choosing the best suitable network from a set of available access networks. Some of the weighty issues in 4G wireless networks are fastness and seamlessness in handover process. This paper therefore, proposes a handover technique based on movement prediction in wireless mobile (WiMAX and LTE-A) environment. The technique enables the system to predict signal quality between the UE and Radio Base Stations (RBS)/Access Points (APs) in two different networks. Prediction is achieved by employing the Markov Decision Process Model (MDPM) where the movement of the UE is dynamically estimated and averaged to keep track of the signal strength of mobile users. With the help of the prediction, layer-3 handover activities are able to occur prior to layer-2 handover, and therefore, total handover latency can be reduced. The performances of various handover approaches influenced by different metrics (mobility velocities) were evaluated. The results presented demonstrate good accuracy the proposed method was able to achieve in predicting the next signal level by reducing the total handover latency

Holistic network selection using dynamic weights to achieve personalized ABC

Network selection technique will be one of the deciding factors in determining the success of 4G network. This is because even though the 4G network technologies such as IEEE 802.16m and LTE-A is capable of providing 4G performance, the benefits that these technologies extol will not trickle down to the mobile nodes (MN) involved if the network selection method is inefficient. High speed MNs will be a feature of 4G networks as these networks are capable of supporting MNs that move at a speed of up to 250km/hr. Therefore, a network selection mechanism that takes into account MN's mobility scenario is absolutely necessary. Network communication environment that is heterogeneous, whereby MNs with multiple interfaces can connect to is also becoming the norm. This means network selection method that can provide personalized Always Best Connected (ABC) is vital in maximizing the potential of heterogeneous candidate networks (CN) in fulfilling user's needs. This paper discusses how this can be attained using a network selection methodology that encompasses dynamic weights and detailed user requirement data collection

Estimation of Signal Level Evolution for Handover in Networks with Femtocells

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

SCALABLE AND EFFICIENT VERTICAL HANDOVER DECISION ALGORITHMS IN VEHICULAR NETWORK CONTEXTS

A finales de los años noventa, y al comienzo del nuevo milenio, las redes inalámbricas han evolucionado bastante, pasando de ser sólo una tecnología prometedora para convertirse en un requisito para las actividades cotidianas en las sociedades desarrolladas. La infraestructura de transporte también ha evolucionado, ofreciendo comunicación a bordo para mejorar la seguridad vial y el acceso a contenidos de información y entretenimiento. Los requisitos de los usuarios finales se han hecho dependientes de la tecnología, lo que significa que sus necesidades de conectividad han aumentado debido a los diversos requisitos de las aplicaciones que se ejecutan en sus dispositivos móviles, tales como tabletas, teléfonos inteligentes, ordenadores portátiles o incluso ordenadores de abordo (On-Board Units (OBUs)) dentro de los vehículos. Para cumplir con dichos requisitos de conectividad, y teniendo en cuenta las diferentes redes inalámbricas disponibles, es necesario adoptar técnicas de Vertical Handover (VHO) para cambiar de red de forma transparente y sin necesidad de intervención del usuario. El objetivo de esta tesis es desarrollar algoritmos de decisión (Vertical Handover Decision Algorithms (VHDAs)) eficientes y escalables, optimizados para el contexto de las redes vehiculares. En ese sentido se ha propuesto, desarrollado y probado diferentes algoritmos de decisión basados en la infraestructura disponible en las actuales, y probablemente en las futuras, redes inalámbricas y redes vehiculares. Para ello se han combinado diferentes técnicas, métodos computacionales y modelos matemáticos, con el fin de garantizar una conectividad apropiada, y realizando el handover hacia las redes más adecuadas de manera a cumplir tanto con los requisitos de los usuarios como los requisitos de las aplicaciones. Con el fin de evaluar el contexto, se han utilizado diferentes herramientas para obtener información variada, como la disponibilidad de la red, el estado de la red, la geolocalizaciónMárquez Barja, JM. (2012). SCALABLE AND EFFICIENT VERTICAL HANDOVER DECISION ALGORITHMS IN VEHICULAR NETWORK CONTEXTS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17869Palanci