Slotted Aloha for Networked Base Stations

We study multiple base station, multi-access systems in which the user-base station adjacency is induced by geographical proximity. At each slot, each user transmits (is active) with a certain probability, independently of other users, and is heard by all base stations within the distance $r$. Both the users and base stations are placed uniformly at random over the (unit) area. We first consider a non-cooperative decoding where base stations work in isolation, but a user is decoded as soon as one of its nearby base stations reads a clean signal from it. We find the decoding probability and quantify the gains introduced by multiple base stations. Specifically, the peak throughput increases linearly with the number of base stations $m$ and is roughly $m/4$ larger than the throughput of a single-base station that uses standard slotted Aloha. Next, we propose a cooperative decoding, where the mutually close base stations inform each other whenever they decode a user inside their coverage overlap. At each base station, the messages received from the nearby stations help resolve collisions by the interference cancellation mechanism. Building from our exact formulas for the non-cooperative case, we provide a heuristic formula for the cooperative decoding probability that reflects well the actual performance. Finally, we demonstrate by simulation significant gains of cooperation with respect to the non-cooperative decoding.Comment: conference; submitted on Dec 15, 201

Design of thick film microstrip lowpass filters

This paper presents the CAD of RF and microwave filters such as shielded single layer thick film lowpass filters for wireless communication systems. The performances of the filter were investigated and the optimisation of filter elements was performed

Sparse MRI with a Markov Random Field Prior for the Subband Coefficients

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Integrative clustering by non-negative matrix factorization can reveal coherent functional groups from gene profile data

Recent developments in molecular biology and tech- niques for genome-wide data acquisition have resulted in abun- dance of data to profile genes and predict their function. These data sets may come from diverse sources and it is an open question how to commonly address them and fuse them into a joint prediction model. A prevailing technique to identify groups of related genes that exhibit similar profiles is profile-based clustering. Cluster inference may benefit from consensus across different clustering models. In this paper we propose a technique that develops separate gene clusters from each of available data sources and then fuses them by means of non-negative matrix factorization. We use gene profile data on the budding yeast S. cerevisiae to demonstrate that this approach can successfully integrate heterogeneous data sets and yields high-quality clusters that could otherwise not be inferred by simply merging the gene profiles prior to clustering

COMPACT LEFT-HANDED DUAL-BAND FILTERS BASED ON SHUNDTED STUB RESONATORS

In this paper, super-compact microstrip dual-band resonator is presented, designed using the superposition of two simple left-handed (LH) resonators with single shunt stub. The proposed resonator exhibits spurious response in wide frequency range and therefore allows construction of dual-band filters using the superposition principle. The equivalent circuit model of the proposed resonator is crated and the influence of different geometrical parameters to the performances of the resonator are analyzed in details. As an examples, two dual-band filters that operate simultaneously at the WiMAX frequency bands are designed

Integrative clustering by non-negative matrix factorization can reveal coherent functional groups from gene profile data

Recent developments in molecular biology and tech- niques for genome-wide data acquisition have resulted in abun- dance of data to profile genes and predict their function. These data sets may come from diverse sources and it is an open question how to commonly address them and fuse them into a joint prediction model. A prevailing technique to identify groups of related genes that exhibit similar profiles is profile-based clustering. Cluster inference may benefit from consensus across different clustering models. In this paper we propose a technique that develops separate gene clusters from each of available data sources and then fuses them by means of non-negative matrix factorization. We use gene profile data on the budding yeast S. cerevisiae to demonstrate that this approach can successfully integrate heterogeneous data sets and yields high-quality clusters that could otherwise not be inferred by simply merging the gene profiles prior to clustering

Resolved stellar populations of dwarf galaxies in the Centaurus A/M83 group

Dwarf galaxies, fundamental ingredients of galactic structures in our Universe, are ubiquitous and surprisingly heterogeneous systems. The study of such objects in nearby groups is a powerful way of investigating their formation and evolutionary mechanisms. The Centaurus A/M83 group is denser and in a more advanced evolutionary phase than our own Local Group, thus being an appealing target for the study of dwarf galaxies. Its more than 50 dwarf members, with different morphologies and stellar contents, can still be resolved into individual stars (at an average Galactocentric distance of ~4 Mpc). We use optical (HST/ACS) and near-infrared (VLT/ISAAC) photometric data to derive physical properties and evolutionary histories for sixteen dwarfs in this group. Specifically, the predominantly old populations of our target early-type dwarfs show metallicity contents that resemble what is found for Local Group members. However, they intriguingly contain lower intermediate-age population fractions than those found in morphologically similar dwarfs around the Milky Way, thus being more comparable to the M31 companions. We also apply our analysis techniques to the deeper photometric data available for M31 early-type dwarfs. The star formation histories derived for our star-forming late-type dwarf targets reveal that the star formation is quenched for galaxies currently found in the densest group regions. The time-dependent spatial distribution of their stellar populations points toward a stochastic star formation mode in these objects. Our results show that the evolution of dwarf galaxies depends on their mass but that it is, at the same time, heavily influenced by the surrounding environment. The Centaurus A/M83 group, along with other nearby galaxy groups, deserves further attention in order for us to ultimately gain deeper insights into the processes that regulate the evolution of dwarf galaxies