Search results for "networks"
showing 10 items of 3260 documents
A Geometrical Channel Model for MIMO Mobile-to-Mobile Fading Channels in Cooperative Networks
2009
This paper deals with the modeling and analysis of narrowband multiple-input multiple-output (MIMO) mobile- to-mobile (M2M) fading channels in relay-based cooperative networks. Non-line-of-sight (NLOS) propagation conditions are assumed in the transmission links from the source mobile station to the destination mobile station via the mobile relay. A stochastic narrowband MIMO M2M reference channel model is derived from the geometrical three-ring scattering model, where it is assumed that an infinite number of local scatterers surround the source mobile station, the mobile relay, and the destination mobile station. The complex channel gains associated with the new reference channel model are…
Focal Cortical Lesions Induce Bidirectional Changes in the Excitability of Fast Spiking and Non Fast Spiking Cortical Interneurons
2014
A physiological brain function requires neuronal networks to operate within a well-defined range of activity. Indeed, alterations in neuronal excitability have been associated with several pathological conditions, ranging from epilepsy to neuropsychiatric disorders. Changes in inhibitory transmission are known to play a key role in the development of hyperexcitability. However it is largely unknown whether specific interneuronal subpopulations contribute differentially to such pathological condition. In the present study we investigated functional alterations of inhibitory interneurons embedded in a hyperexcitable cortical circuit at the border of chronically induced focal lesions in mouse …
A flexible and reconfigurable 5G networking architecture based on context and content information
2017
The need for massive content delivery is a consolidated trend in mobile communications, and will even increase for next years. Moreover, while 4G maturity and evolution is driven by video contents, next generation (5G) networks will be dominated by heterogeneous data and additional massive diffusion of Internet of Things (IoT). The current network architecture is not sufficient to cope with such traffic, which is heterogeneous in terms of latency and QoS requirements, and variable in space and time. This paper proposes architectural advances to endow the network with the necessary flexibility helping to adapt to these varying traffic needs by providing content and communication services whe…
Designing the 5G network infrastructure: a flexible and reconfigurable architecture based on context and content information
2018
5G networks will have to offer extremely high volumes of content, compared to those of today’s. Moreover, they will have to support heterogeneous traffics, including machine-to-machine, generated by a massive volume of Internet-of-Things devices. Traffic demands will be variable in time and space. In this work, we argue that all this can be achieved in a cost-effective way if the network is flexible and reconfigurable. We present the Flex5Gware network architecture, designed to meet the above requirements. Moreover, we discuss the links between flexibility and reconfigurability, on the one side, and context awareness and content awareness, on the other; we show how two of the building…
Action in Perception: Prominent Visuo-Motor Functional Symmetry in Musicians during Music Listening.
2015
Musical training leads to sensory and motor neuroplastic changes in the human brain. Motivated by findings on enlarged corpus callosum in musicians and asymmetric somatomotor representation in string players, we investigated the relationship between musical training, callosal anatomy, and interhemispheric functional symmetry during music listening. Functional symmetry was increased in musicians compared to nonmusicians, and in keyboardists compared to string players. This increased functional symmetry was prominent in visual and motor brain networks. Callosal size did not significantly differ between groups except for the posterior callosum in musicians compared to nonmusicians. We conclude…
Learning automata based energy-efficient AI hardware design for IoT applications
2020
Energy efficiency continues to be the core design challenge for artificial intelligence (AI) hardware designers. In this paper, we propose a new AI hardware architecture targeting Internet of Things applications. The architecture is founded on the principle of learning automata, defined using propositional logic. The logic-based underpinning enables low-energy footprints as well as high learning accuracy during training and inference, which are crucial requirements for efficient AI with long operating life. We present the first insights into this new architecture in the form of a custom-designed integrated circuit for pervasive applications. Fundamental to this circuit is systematic encodin…
Fire and phylogenetic structure of soil microbial communities in Mediterranean ecosystems
2017
Tesis llevada a cabo para conseguir el grado de Doctor por la Universidad de Valencia.--2018-02-21.--Sobresaliente Cum laudem
Radio environment map estimation based on communication cost modeling for heterogeneous networks
2017
Los mapas del entorno radioeléctrico pueden ser una poderosa herramienta para lograr una asignación de recursos eficiente y consciente del contexto en las redes heterogéneas 5G. En este trabajo, consideramos una red heterogénea formada por una red celular tradicional y una red de sensores inalámbricos. El papel de la red de sensores inalámbricos es estimar el mapa del entorno radioeléctrico de la célula utilizando una técnica de interpolación geoestadística denominada Kriging. En un trabajo anterior se propuso un algoritmo de agrupación distribuida de sensores para reducir la complejidad de la estimación. En nuestra contribución, el proceso de formación de clústeres se modifica para incluir…
Distributed Clustering Algorithm for Spatial Field Reconstruction in Wireless Sensor Networks
2015
En este trabajo, consideramos el problema de la estimación espacial distribuida para la reconstrucción del campo radio en redes de sensores inalámbricos. Para estimar el campo, se utiliza una técnica geoestadística llamada kriging. La estimación espacial centralizada con un gran número de sensores conllevan un elevado coste computacional y gasto de energía. Presentamos un novedoso algoritmo de clustering distribuido para estimar mapas de interferencia espacial, que son esenciales para las operaciones y la gestión de las futuras redes inalámbricas. En este algoritmo, los clústeres de sensores se forman de forma adaptativa mediante la minimización de la varianza de kriging. El cálculo del sem…
A low complexity distributed cluster based algorithm for spatial prediction
2017
Los mapas del entorno radioeléctrico (REM) pueden ser una herramienta esencial para numerosas aplicaciones en las futuras redes inalámbricas 5G. En este trabajo, empleamos un popular método geoestadístico llamado kriging ordinario para estimar el REM de un área cubierta por un eNodeB equipado con múltiples antenas. Los sensores inalámbricos se distribuyen por el área de interés y se organizan clústeres adaptativos de sensores para mejorar la calidad de la estimación del canal. En este trabajo, modificamos el algoritmo de clustering distribuido propuesto en un trabajo anterior para reducir la complejidad de la predicción de kriging. Se realizan simulaciones para detallar la técnica de formac…