A Novel Antenna Selection Scheme for Spatially Correlated Massive MIMO Uplinks with Imperfect Channel Estimation

We propose a new antenna selection scheme for a massive MIMO system with a single user terminal and a base station with a large number of antennas. We consider a practical scenario where there is a realistic correlation among the antennas and imperfect channel estimation at the receiver side. The proposed scheme exploits the sparsity of the channel matrix for the effective selection of a limited number of antennas. To this end, we compute a sparse channel matrix by minimising the mean squared error. This optimisation problem is then solved by the well-known orthogonal matching pursuit algorithm. Widely used models for spatial correlation among the antennas and channel estimation errors are considered in this work. Simulation results demonstrate that when the impacts of spatial correlation and imperfect channel estimation introduced, the proposed scheme in the paper can significantly reduce complexity of the receiver, without degrading the system performance compared to the maximum ratio combining.Comment: in Proc. IEEE 81st Vehicular Technology Conference (VTC), May 2015, 6 pages, 5 figure

Deformation of the Fermi surface in the extended Hubbard model

The deformation of the Fermi surface induced by Coulomb interactions is investigated in the t-t'-Hubbard model. The interplay of the local U and extended V interactions is analyzed. It is found that exchange interactions V enhance small anisotropies producing deformations of the Fermi surface which break the point group symmetry of the square lattice at the Van Hove filling. This Pomeranchuck instability competes with ferromagnetism and is suppressed at a critical value of U(V). The interaction V renormalizes the t' parameter to smaller values what favours nesting. It also induces changes on the topology of the Fermi surface which can go from hole to electron-like what may explain recent ARPES experiments.Comment: 5 pages, 4 ps figure

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2

Simulation study of the two-dimensional Burridge-Knopoff model of earthquakes

Spatiotemporal correlations of the two-dimensional spring-block (Burridge-Knopoff) model of earthquakes are extensively studied by means of numerical computer simulations. The model is found to exhibit either ``subcritical'' or ``supercritical'' behavior, depending on the values of the model parameters. Transition between these regimes is either continuous or discontinuous. Seismic events in the ``subcritical'' regime and those in the ``supercritical'' regime at larger magnitudes exhibit universal scaling properties. In the ``supercritical'' regime, eminent spatiotemporal correlations, {\it e.g.}, remarkable growth of seismic activity preceding the mainshock, arise in earthquake occurrence, whereas such spatiotemporal correlations are significantly suppressed in the ``subcritical'' regime. Seismic activity is generically suppressed just before the mainshock in a close vicinity of the epicenter of the upcoming event while it remains to be active in the surroundings (the Mogi doughnut). It is also observed that, before and after the mainshock, the apparent $B$-value of the magnitude distribution decreases or increases in the ``supercritical'' or ``subcritical'' regimes, respectively. Such distinct precursory phenomena may open a way to the prediction of the upcoming large event

Doubly Robust Inference when Combining Probability and Non-probability Samples with High-dimensional Data

Non-probability samples become increasingly popular in survey statistics but may suffer from selection biases that limit the generalizability of results to the target population. We consider integrating a non-probability sample with a probability sample which provides high-dimensional representative covariate information of the target population. We propose a two-step approach for variable selection and finite population inference. In the first step, we use penalized estimating equations with folded-concave penalties to select important variables for the sampling score of selection into the non-probability sample and the outcome model. We show that the penalized estimating equation approach enjoys the selection consistency property for general probability samples. The major technical hurdle is due to the possible dependence of the sample under the finite population framework. To overcome this challenge, we construct martingales which enable us to apply Bernstein concentration inequality for martingales. In the second step, we focus on a doubly robust estimator of the finite population mean and re-estimate the nuisance model parameters by minimizing the asymptotic squared bias of the doubly robust estimator. This estimating strategy mitigates the possible first-step selection error and renders the doubly robust estimator root-n consistent if either the sampling probability or the outcome model is correctly specified

The Degeneracy of Galaxy Formation Models

We develop a new formalism for modeling the formation and evolution of galaxies within a hierarchical universe. Similarly to standard semi-analytical models we trace galaxies inside dark-matter merger-trees. The formalism includes treatment of feedback, star-formation, cooling, smooth accretion, gas stripping in satellite galaxies, and merger-induced star bursts. However, unlike in other models, each process is assumed to have an efficiency which depends only on the host halo mass and redshift. This allows us to describe the various components of the model in a simple and transparent way. By allowing the efficiencies to have any value for a given halo mass and redshift, we can easily encompass a large range of scenarios. To demonstrate this point, we examine several different galaxy formation models, which are all consistent with the observational data. Each model is characterized by a different unique feature: cold accretion in low mass haloes, zero feedback, stars formed only in merger-induced bursts, and shutdown of star-formation after mergers. Using these models we are able to examine the degeneracy inherent in galaxy formation models, and look for observational data that will help to break this degeneracy. We show that the full distribution of star-formation rates in a given stellar mass bin is promising in constraining the models. We compare our approach in detail to the semi-analytical model of De Lucia & Blaizot. It is shown that our formalism is able to produce a very similar population of galaxies once the same median efficiencies per halo mass and redshift are being used. We provide a public version of the model galaxies on our web-page, along with a tool for running models with user-defined parameters. Our model is able to provide results for a 62.5 h^{-1} Mpc box within just a few seconds.Comment: Accepted for publication in MNRAS. Fig 6 & 7 corrected. For the project page which allows running your own model, see http://www.mpa-garching.mpg.de/galform/sesam

Spatiotemporal correlations of earthquakes in the continuum limit of the one-dimensional Burridge-Knopoff model

Spatiotemporal correlations of the one-dimensional spring-block (Burridge-Knopoff) model of earthquakes, either with or without the viscosity term, are studied by means of numerical computer simulations. The continuum limit of the model is examined by systematically investigating the model properties with varying the block-size parameter a toward a\to 0. The Kelvin viscosity term is introduced so that the model dynamics possesses a sensible continuum limit. In the presence of the viscosity term, many of the properties of the original discrete BK model are kept qualitatively unchanged even in the continuum limit, although the size of minimum earthquake gets smaller as a gets smaller. One notable exception is the existence/non-existence of the doughnut-like quiescence prior to the mainshock. Although large events of the original discrete BK model accompany seismic acceleration together with a doughnut-like quiescence just before the mainshock, the spatial range of the doughnut-like quiescence becomes narrower as a gets smaller, and in the continuum limit, the doughnut-like quiescence might vanish altogether. The doughnut-like quiescence observed in the discrete BK model is then a phenomenon closely related to the short-length cut-off scale of the model

Recent Developments in Maser Theory

This review covers selected developments in maser theory since the previous meeting, "Cosmic Masers: From Proto-Stars to Black Holes" (Migenes & Reid 2002). Topics included are time variability of fundamental constants, pumping of OH megamasers and indicators for differentiating disks from bi-directional outflows.Comment: Review presented at IAU symposium 242, "Astrophysical Masers and their Environments

Fermion-Higgs model with strong Wilson-Yukawa coupling in two dimensions

The fermion mass spectrum is studied in the quenched approximation in the strong coupling vortex phase (VXS) of a globally U(1)$_L \otimes$U(1)$_R$ symmetric scalar-fermion model in two dimensions. In this phase fermion doublers can be completely removed from the physical spectrum by means of a strong Wilson-Yukawa coupling. The lowest lying fermion spectrum in this phase consists most probably only of a massive Dirac fermion which has charge zero with respect to the $U(1)_L$ group. We give evidence that the fermion which is charged with respect to that subgroup is absent in the VXS phase. When the $U(1)_L$ gauge fields are turned on, the neutral fermion may couple chirally to the massive vector boson state in the confinement phase. The outcome is very similar to our findings in the strong coupling symmetric phase (PMS) of fermion-Higgs models with Wilson-Yukawa coupling in four dimensions, with the exception that in four dimensions the neutral fermion does most probably decouple from the bosonic bound states.Comment: 21 pages, 6 postscript figures (appended), Amsterdam ITFA 92-21, HLRZ J\"ulich 92-5

Peaks in the cosmological density field: parameter constraints from 2dF Galaxy Redshift Survey data

We use the number density of peaks in the smoothed cosmological density field taken from the 2dF Galaxy Redshift Survey to constrain parameters related to the power spectrum of mass fluctuations, n (the spectral index), dn/d(lnk) (rolling in the spectral index), and the neutrino mass, m_nu. In a companion paper we use N-body simulations to study how the peak density responds to changes in the power spectrum, the presence of redshift distortions and the relationship between galaxies and dark matter halos. In the present paper we make measurements of the peak density from 2dF Galaxy Redshift Survey data, for a range of smoothing filter scales from 4-33 h^-1 Mpc. We use these measurements to constrain the cosmological parameters, finding n=1.36 (+0.75)(-0.64), m_nu < 1.76 eV, dn/d(lnk)=-0.012 (+0.192)(-0.208), at the 68 % confidence level, where m_nu is the total mass of three massive neutrinos. At 95% confidence we find m_nu< 2.48 eV. These measurements represent an alternative way to constrain cosmological parameters to the usual direct fits to the galaxy power spectrum, and are expected to be relatively insensitive to non-linear clustering evolution and galaxy biasing.Comment: Accepted for Publication in MNRAS on Sept 25, 2009. Abstract modified to remove LaTex markup