Stefania Sardellitti

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Mobile cloud computing is offering a very powerful storage and computational facility to enhance the capabilities of resource-constrained mobile handsets. However, full exploitation of the cloud computing capabilities can be achieved only if the allocation of radio and computational capabilities is performed jointly. In this paper, we propose a method to(More)
Current estimates of mobile data traffic in the years to come foresee a 1,000 increase of mobile data traffic in 2020 with respect to 2010, or, equivalently, a doubling of mobile data traffic every year. This unprecedented growth demands a significant increase of wireless network capacity. Even if the current evolution of fourth-generation (4G) systems and,(More)
Migrating computational intensive tasks from mobile devices to more resourceful cloud servers is a promising technique to increase the computational capacity of mobile devices while saving their battery energy. In this paper, we consider an MIMO multicell system where multiple mobile users (MUs) ask for computation offloading to a common cloud server. We(More)
Consensus algorithms have generated a lot of interest due to their ability to compute globally relevant statistics by only exploiting local communications among sensors. However, when implemented over wireless sensor networks, the inherent iterative nature of consensus algorithms may cause a large energy consumption. Hence, to make consensus algorithms(More)
Femtocells are receiving considerable interest in mobile communications as a strategy to overcome the indoor coverage problems as well as to improve the efficiency of current macrocell systems. One of the most critical issues in femtocells is the potential interference between nearby femtocells and from femtocells to macrocells or to mobile handsets. In(More)
The association of a graph representation to large datasets is one of key steps in graph-based learning methods. The aim of this paper is to propose an efficient strategy for learning the graph topology from signals defined over the vertices of a graph, under a signal band-limited (either exactly or only approximately so) assumption, which corresponds to(More)
Distributed consensus algorithms have recently gained large interest in sensor networks as a way to achieve globally optimal decisions in a totally decentralized way, that is, without the need of sending all the data collected by the sensors to a fusion center. However, distributed algorithms are typically iterative and they suffer from convergence time and(More)
Wireless sensor networks (WSN) are receiving a lot of attention from both the theoretical and application sides, in view of the many applications spanning from environmental monitoring, as a tool to control physical parameters such as temperature, vibration, pressure, or pollutant concentration, to the monitoring of civil infrastructures, such as roads,(More)
In iterative data-detection and channel-estimation algorithms, the channel estimator and the data detector recursively exchange information in order to improve the system performance. While a vast bulk of the available literature demonstrates the merits of iterative schemes through computer simulations, in this paper analytical results on the performance of(More)