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Ítem A statistical channel model for on body Area networks in Ultra Wide Band Communications(IEEE, 2009-09-10) Cardona, NarcisThis paper presents a novel statistical channel model for Ultra Wide Band Communications when On Body Area Networks Environments are considered. Results and Analysis of frequency measurements from 1GHz to 12GHz for body area networks are described. We propose a modified Saleh-Valenzuela statistical channel model considering different assumptions for small scale statistics in the model. Results show that the small scale amplitude follows a log normal distribution, the inter arrival times between multi path components are poisson process; the decay factor, the number of paths and clusters follow exponential distributions. The proposed model can be used for realistic simulations for on body communications in Ultra Wide Band systems. © 2009 IEEE.Ítem A novel SNR estimation algorithm for MB OFDM ultra wide band communications(IEEE, 2014-09-10) anavarro@icesi.edu.coIn this paper we propose a novel signal to noise ratio algorithm based on the moments of the received signal. The novel algorithm has been designed for Multi Band Orthogonal Frequency Division Multiplexing (MB-OFDM) communication systems in ultra wide band channels. The proposed algorithm is a switched estimator that uses two equation models, one is for large SNR scale and the other for low SNR scale. The proposed model can be used for SNR estimation in adaptive modulation and channel estimation and link quality control in MB OFDM systems. This algorithm can be implemented in receivers with simple structures. The performance of the proposed SNR estimation algorithm and its comparison with other SNR estimators was achieved through simulations. © 2009 IEEE.Ítem Interference detection in centralized cooperative spectrum sensing from sub-Nyquist samples(IEEE, 2016-12-21) Sosa, AnibalWideband spectrum sensing plays a crucial role in a number of applications among which the cognitive radio (CR) is one of the most prominent. In this work we consider a scenario where the wide band of interest is comprised of multiple communication channels occupied by several independent transmissions. Due to the propagation conditions, some of the transmissions can cause potential interference by occupying the same channel at different locations. In order to alleviate the effect of such interference, we employ a network of distributed sensing nodes that sample the wideband signal at sub-Nyquist rate and share the acquired data with the fusion center. We show that using the structure of the correlations between the sub-Nyquist samples obtained at different sensors, we can detect the presence of potential in-channel interference. We present a concrete approach for estimation of the central frequencies of the channels in which it occurs and demonstrate its effectiveness in simulations.