A Multi-Layer Parametric Approach to Maximize the Access Probability of Mobile Networks

Abstract

Next-generation mobile networks (5G) are defined to provide access in the framework of heterogeneous systems where it is crucial to have “always on” and “everywhere connectivity” capabilities. This is of fundamental importance even in 4G mobile systems, down to 3G and also Wi-Fi and WiMAX. In order to guarantee access to users with handheld devices equipped with multiple radio interfaces, an automated and reconfigurable tool for selecting the best network to be connected with is needed. This should be achieved by avoiding service outages. Current vertical handovers, i.e., switching from a network to another, are essentially based on power received levels and often do not avoid temporary service outages. We propose in this paper a procedure to access mobile networks by sensing multiple performance parameters related to networks available in the considered area. We target at maximizing the probability of accessing the wireless medium despite the technology used. We develop an algorithm, based on dynamic programming, able to select the most suitable network. We present the performance of the proposed algorithm both on the basis of computer simulations and on tests performed in an Arduino-based hardware platform

Pressure effects on the X-ray intrinsic position resolution in noble gases and mixtures

“…In particular, the electrons transverse diffusion (parallel to readout) will blurry the reconstructed image. The transverse diffusion (σ T ) for pressures from 1 to 10 bar was calculated by using Magboltz [15] being the results presented in figure 3 for a mixture of Ar/20%CO 2 (a) and Xe/10%CO 2 (b). A fit to the expected 1/ √ P behaviour [5] is overlaid.…”

“…For the calculations a software tool which includes secondary processes like X-ray fluorescence, Auger, Coster-Kronig and shake-off was used: Degrad [10]. This software tool, developed by one of us (S. Biagi), is at the moment able to calculate the atomic cascade initiated by X-ray photons or electrons interacting in the gas, returning the number of ionizations, excitations and the position of each thermalized electron [11].…”

“…For each simulation conditions, 200.000 events were generated using Degrad 2.13 [10]. All events were forced to interact at the centre of the detector (X,Y,Z=0,0,0) in order to simulate an infinitesimal point-like interaction.…”

“…The effect of the transverse diffusion during the electron drift was simulated by considering the spread of the electrons according to a Gaussian probability distribution with the center at the electron position and standard deviation equal to the transverse diffusion value, as computed by Magboltz [15].…”