Las TIC como factor de inclusión de las zonas rurales marginales

El acortamiento de la brecha digital impulsado por la introducción de tecnologías (TIC) en grupos\nmarginales tiene un potencial de gran impacto social. Proveer el acceso a Internet en poblados aislados\ndebería ser prioridad de todo programa de desarrollo. Pero sólo tendría sentido, si sus usuarios reconocen\nbeneficios en sus vidas cotidianas (1) para poder adueñarse de la experiencia

On the Outage Probability of the Full-Duplex Interference-Limited Relay Channel

In this paper, we study the performance, in terms of the asymptotic error probability, of a user which communicates with a destination with the aid of a full-duplex in-band relay. We consider that the network is interference-limited, and interfering users are distributed as a Poisson point process. In this case, the asymptotic error probability is upper bounded by the outage probability (OP). We investigate the outage behavior for well-known cooperative schemes, namely, decode-and-forward (DF) and compress-and-forward (CF) considering fading and path loss. For DF we determine the exact OP and develop upper bounds which are tight in typical operating conditions. Also, we find the correlation coefficient between source and relay signals which minimizes the OP when the density of interferers is small. For CF, the achievable rates are determined by the spatial correlation of the interferences, and a straightforward analysis isn't possible. To handle this issue, we show the rate with correlated noises is at most one bit worse than with uncorrelated noises, and thus find an upper bound on the performance of CF. These results are useful to evaluate the performance and to optimize relaying schemes in the context of full-duplex wireless networks.Comment: 30 pages, 4 figures. Final version. To appear in IEEE JSAC Special Issue on Full-duplex Wireless Communications and Networks, 201

On Fundamental Trade-offs of Device-to-Device Communications in Large Wireless Networks

This paper studies the gains, in terms of served requests, attainable through out-of-band device-to-device (D2D) video exchanges in large cellular networks. A stochastic framework, in which users are clustered to exchange videos, is introduced, considering several aspects of this problem: the video-caching policy, user matching for exchanges, aspects regarding scheduling and transmissions. A family of \emph{admissible protocols} is introduced: in each protocol the users are clustered by means of a hard-core point process and, within the clusters, video exchanges take place. Two metrics, quantifying the "local" and "global" fraction of video requests served through D2D are defined, and relevant trade-off regions involving these metrics, as well as quality-of-service constraints, are identified. A simple communication strategy is proposed and analyzed, to obtain inner bounds to the trade-off regions, and draw conclusions on the performance attainable through D2D. To this end, an analysis of the time-varying interference that the nodes experience, and tight approximations of its Laplace transform are derived.Comment: 33 pages, 9 figures. Updated version, to appear in IEEE Transactions on Wireless Communication

Robust Target Classification Using UWB Sensing^*

Contactless material characterization has received widespread attention in the radar and engineering domains. Specifically, impulsive Ultra Wideband (UWB) systems are a versatile technology for the nondestructive characterization of samples because the scattered field produced by the targets is highly dependent on their composition and shape. After the initial transient response to the transmitted pulse, the scattered signal can be decomposed as a sum of complex exponentials, called complex natural resonances (CNR), which are dependent only on the geometry and composition of the target. Using this result, a classification problem was formulated to discriminate among targets, and a processing strategy was proposed to solve it. In particular, by using spectral decomposition tools, the information obtained from the physical model can be exploited in combination with data-driven learning techniques. Consequently, a classification strategy that is robust to modeling uncertainties and experimental perturbations was designed. To assess the performance of the new scheme, it was tested using both synthetic and experimental data obtained from targets illuminated with a UWB radar. The results showed substantial gains compared to classification using time-domain signals