19,756 research outputs found
An Energy-Aware Protocol for Self-Organizing Heterogeneous LTE Systems
This paper studies the problem of self-organizing heterogeneous LTE systems.
We propose a model that jointly considers several important characteristics of
heterogeneous LTE system, including the usage of orthogonal frequency division
multiple access (OFDMA), the frequency-selective fading for each link, the
interference among different links, and the different transmission capabilities
of different types of base stations. We also consider the cost of energy by
taking into account the power consumption, including that for wireless
transmission and that for operation, of base stations and the price of energy.
Based on this model, we aim to propose a distributed protocol that improves the
spectrum efficiency of the system, which is measured in terms of the weighted
proportional fairness among the throughputs of clients, and reduces the cost of
energy. We identify that there are several important components involved in
this problem. We propose distributed strategies for each of these components.
Each of the proposed strategies requires small computational and
communicational overheads. Moreover, the interactions between components are
also considered in the proposed strategies. Hence, these strategies result in a
solution that jointly considers all factors of heterogeneous LTE systems.
Simulation results also show that our proposed strategies achieve much better
performance than existing ones
Nature of the Quantum Phase Transition in Quantum Compass Model
In this work, we show that the quantum compass model on an square lattice can
be mapped to a fermionic model with local density interaction. We introduce a
mean-field approximation where the most important fluctuations, those
perpendicular to the ordering direction, are taken into account exactly. It is
found that the quantum phase transition point at marks a first order
phase transition. We also show that the mean field result is robust against the
remaining fluctuation corrections up to the second order.Comment: 7 pages, 10 fig
Spectral and optical properties in the antiphase stripe phase of the cuprate superconductors
We investigate the superconducting order parameter, the spectral and optical
properties in a stripe model with spin (charge) domain-derived scattering
potential (). We show that the charge domain-derived scattering
is less effective than the spin scattering on the suppression of
superconductivity. For , the spectral weight concentrates on
the () antinodal region, and a finite energy peak appears in the optical
conductivity with the disappearance of the Drude peak. But for , the spectral weight concentrates on the () nodal region,
and a residual Drude peak exists in the optical conductivity without the finite
energy peak. These results consistently account for the divergent observations
in the ARPES and optical conductivity experiments in several high-
cuprates, and suggest that the "insulating" and "metallic" properties are
intrinsic to the stripe state, depending on the relative strength of the spin
and charge domain-derived scattering potentials.Comment: 7 pages, 4 figure
Efficient Volumetric Method of Moments for Modeling Plasmonic Thin-Film Solar Cells with Periodic Structures
Metallic nanoparticles (NPs) support localized surface plasmon resonances
(LSPRs), which enable to concentrate sunlight at the active layer of solar
cells. However, full-wave modeling of the plasmonic solar cells faces great
challenges in terms of huge computational workload and bad matrix condition. It
is tremendously difficult to accurately and efficiently simulate near-field
multiple scattering effects from plasmonic NPs embedded into solar cells. In
this work, a preconditioned volume integral equation (VIE) is proposed to model
plasmonic organic solar cells (OSCs). The diagonal block preconditioner is
applied to different material domains of the device structure. As a result,
better convergence and higher computing efficiency are achieved. Moreover, the
calculation is further accelerated by two-dimensional periodic Green's
functions. Using the proposed method, the dependences of optical absorption on
the wavelengths and incident angles are investigated. Angular responses of the
plasmonic OSCs show the super-Lambertian absorption on the plasmon resonance
but near-Lambertian absorption off the plasmon resonance. The volumetric method
of moments and explored physical understanding are of great help to investigate
the optical responses of OSCs.Comment: 11 pages, 6 figure
Determining the strange and antistrange quark distributions of the nucleon
The difference between the strange and antistrange quark distributions,
\delta s(x)=s(x)-\sbar(x), and the combination of light quark sea and strange
quark sea, \Delta (x)=\dbar(x)+\ubar(x)-s(x)-\sbar(x), are originated from
non-perturbative processes, and can be calculated using non-perturbative models
of the nucleon. We report calculations of and using
the meson cloud model. Combining our calculations of with
relatively well known light antiquark distributions obtained from global
analysis of available experimental data, we estimate the total strange sea
distributions of the nucleon.Comment: 4 pages, 3 figures; talk given by F.-G. at QNP0
Asset allocation with multiple analysts’ views: a robust approach
Retail investors often make decisions based on professional analysts’ investment recommendations. Although these recommendations contain up-to-date financial information, they are usually expressed in sophisticated but vague forms. In addition, the quality differs from analyst to analyst and recommendations may even be mutually conflicting. This paper addresses these issues by extending the Black–Litterman (BL) method and developing a multi-analyst portfolio selection method, balanced against any over-optimistic forecasts. Our methods accommodate analysts’ ambiguous investment recommendations and the heterogeneity of data from disparate sources. We prove the validity of our model, using an empirical analysis of around 1000 daily financial newsletters collected from two top 10 Taiwanese brokerage firms over a 2-year period. We conclude that analysts’ views contribute to the investment allocation process and enhance the portfolio performance. We confirm that the degree of investors’ confidence in these views influences the portfolio outcome, thus extending the idea of the BL model and improving the practicality of robust optimisation
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