pwc-archive/papers-with-abstracts huggingface dataset:
Prototyping with SDR: a quick way to play with next-gen communications systems
Date: 2018-03-20 00:00:00

In this paper we present our approach regarding the implementation of new
wireless radio receiver exploiting filterbank techniques, using a
software-development driven approach. Since most of the common radio
communications systems share a similar structure, this can be exploited
creating a framework which provides a generic layout and tools to construct a
reconfigurable transmitter and/or receiver. By combining the use of the
Universal Software Radio Peripheral version 2 (USRP2) with a generic
object-oriented framework of our own built on top of the GNU Radio software
framework, we have been able to quickly implement a working proof of concept of
an Uplink (UL) Filterbank Multicarrier (FBMC) receiver, both for SingleInput
Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) scenario, within
the project of the 7th European framework called PHYDYAS. We described here the
methodology we have applied from software engineering in order to build this
demonstrator, which shows the suitability of using Software Defined Radio (SDR)
technologies for fast prototyping of new wireless communication systems.
Evolution of Spatial and Multicarrier Scheduling: Towards Multi-cell Scenario
Date: 2018-03-20 00:00:00
Tasks: Management, Scheduling

OFDMA systems are considered as the promising multiple access scheme of next
generation multi-cellular wireless systems. In order to ensure the optimum
usage of radio resources, OFDMA radio resource management algorithms have to
maximize the allocated power and rate of the different subchannels to the users
taking also into account the generated co-channel interference between
neighboring cells, which affects the received Quality of Service. This paper
discusses various schemes for power distribution schemes in multiple co-channel
cells. These schemes include centralized and distributed solutions, which may
involve various degrees of complexity and related overhead and may employ
procedures such as linear programming. Finally, the paper introduces a new
solution that uses a network flow model to solve the maximization of the
multi-cell system sum rate. The application of spatial beamforming at each cell
is suggested in order to better cope with interference.
A Low Complexity Space-Frequency Multiuser Scheduling Algorithm
Date: 2018-03-20 00:00:00
Tasks: Diversity, Scheduling

This work presents a resource allocation algorithm in K-user, M-subcarrier
and NT-antenna systems for on-line scheduling. To exploit temporal diversity
and to reduce complexity, the ergodic sum rate is maximized instead of the
instantaneous one. Dual optimization is applied to further diminish complexity
together with a stochastic approximation, which is more suitable for online
algorithms. Weighted sum rate is considered so that users can be either
prioritized by higher layers or differentiated by proportional rate
constraints. The performance and complexity of this algorithm is compared with
well-known benchmarks and also evaluated under real system conditions for the
MIMO Broadcast channel.
Disentangling top-down vs. bottom-up and low-level vs. high-level influences on eye movements over time
Date: 2018-05-17 00:00:00

Bottom-up and top-down, as well as low-level and high-level factors influence
where we fixate when viewing natural scenes. However, the importance of each of
these factors and how they interact remains a matter of debate. Here, we
disentangle these factors by analysing their influence over time. For this
purpose we develop a saliency model which is based on the internal
representation of a recent early spatial vision model to measure the low-level
bottom-up factor. To measure the influence of high-level bottom-up features, we
use a recent DNN-based saliency model. To account for top-down influences, we
evaluate the models on two large datasets with different tasks: first, a
memorisation task and, second, a search task. Our results lend support to a
separation of visual scene exploration into three phases: The first saccade, an
initial guided exploration characterised by a gradual broadening of the
fixation density, and an steady state which is reached after roughly 10
fixations. Saccade target selection during the initial exploration and in the
steady state are related to similar areas of interest, which are better
predicted when including high-level features. In the search dataset, fixation
locations are determined predominantly by top-down processes. In contrast, the
first fixation follows a different fixation density and contains a strong
central fixation bias. Nonetheless, first fixations are guided strongly by
image properties and as early as 200 ms after image onset, fixations are better
predicted by high-level information. We conclude that any low-level bottom-up
factors are mainly limited to the generation of the first saccade. All saccades
are better explained when high-level features are considered, and later this
high-level bottom-up control can be overruled by top-down influences.
Convolution, Product and Correlation Theorems for Simplified Fractional Fourier Transform: A Mathematical Investigation
Date: 2018-03-20 00:00:00

The notion of fractional Fourier transform (FrFT) has been used and
investigated for many years by various research communities, which finds
widespread applications in many diverse fields of research study. The potential
applications includes ranging from quantum physics, harmonic analysis, optical
information processing, pattern recognition to varied allied areas of signal
processing. Many significant theorems and properties of the FrFT have been
investigated and applied to many signal processing applications, most important
among these are convolution, product and correlation theorems. Still many
magnificent research works related to the conventional FrFT lacks the elegance
and simplicity of the convolution, product and correlation theorems similar to
the Euclidean Fourier transform (FT), which for convolution theorem states that
the FT of the convolution of two functions is the product of their respective
FTs. The purpose of this paper is to devise the equivalent elegancy of
convolution, product and correlation theorems, as in the case of Euclidean FT.
Building on the seminal work of Pei et al. and the potential of the simplified
fractional Fourier transform (SmFrFT), a detailed mathematical investigation is
established to present an elegant definition of convolution, product and
correlation theorems in the SmFrFT domain, along with their associated
important properties. It has been shown that the established theorems along
with their associated properties very nicely generalizes to the classical
Euclidean FT.
Nonlinear dynamics and fluctuations in biological systems (Habilitation thesis)
Date: 2018-03-20 00:00:00

The present habilitation thesis in theoretical biological physics addresses
two central dynamical processes in cells and organisms: (i) active motility and
motility control and (ii) self-organized pattern formation. The unifying theme
is the nonlinear dynamics of biological function and its robustness in the
presence of strong fluctuations, structural variations, and external
perturbations. We theoretically investigate motility control at the cellular
scale, using cilia and flagella as ideal model system. Cilia and flagella are
highly conserved slender cell appendages that exhibit spontaneous bending
waves. This flagellar beat represents a prime example of a chemo-mechanical
oscillator, which is driven by the collective dynamics of molecular motors
inside the flagellar axoneme. We study the nonlinear dynamics of flagellar
swimming, steering, and synchronization, which encompasses shape control of the
flagellar beat by chemical signals and mechanical forces. Mechanical forces can
synchronize collections of flagella to beat at a common frequency, despite
active motor noise that tends to randomize flagellar synchrony. In Chapter 2,
we present a new physical mechanism for flagellar synchronization by mechanical
self-stabilization that applies to free-swimming flagellated cells. This new
mechanism is independent of direct hydrodynamic interactions between flagella.
Comparison with experimental data provided by experimental collaboration
partners in the laboratory of J. Howard (Yale, New Haven) confirmed our new
mechanism in the model organism of the unicellular green alga Chlamydomonas.
Further, we characterize the beating flagellum as a noisy oscillator. Using a
minimal model of collective motor dynamics, we argue that measured
non-equilibrium fluctuations of the flagellar beat result from stochastic motor
dynamics at the molecular scale. Noise and mechanical coupling are antagonists
...
Testing for Unobserved Heterogeneous Treatment Effects with Observational Data
Authors: Yu-Chin Hsu, Ta-Cheng Huang, Haiqing Xu
Date: 2018-03-20 00:00:00

Unobserved heterogeneous treatment effects have been emphasized in the recent policy evaluation literature (see e.g., Heckman and Vytlacil, 2005). This paper proposes a nonparametric test for unobserved heterogeneous treatment effects in a treatment effect model with a binary treatment assignment, allowing for individuals' self-selection to the treatment. Under the standard local average treatment effects assumptions, i.e., the no defiers condition, we derive testable model restrictions for the hypothesis of unobserved heterogeneous treatment effects. Also, we show that if the treatment outcomes satisfy a monotonicity assumption, these model restrictions are also sufficient. Then, we propose a modified Kolmogorov-Smirnov-type test which is consistent and simple to implement. Monte Carlo simulations show that our test performs well in finite samples. For illustration, we apply our test to study heterogeneous treatment effects of the Job Training Partnership Act on earnings and the impacts of fertility on family income, where the null hypothesis of homogeneous treatment effects gets rejected in the second case but fails to be rejected in the first application.
Water Residence Time Estimation by 1D Deconvolution in the Form of a l2-Regularized Inverse Problem With Smoothness, Positivity and Causality Constraints
Date: 2018-03-20 00:00:00
Tasks: Form

The Water Residence Time distribution is the equivalent of the impulse
response of a linear system allowing the propagation of water through a medium,
e.g. the propagation of rain water from the top of the mountain towards the
aquifers. We consider the output aquifer levels as the convolution between the
input rain levels and the Water Residence Time, starting with an initial
aquifer base level. The estimation of Water Residence Time is important for a
better understanding of hydro-bio-geochemical processes and mixing properties
of wetlands used as filters in ecological applications, as well as protecting
fresh water sources for wells from pollutants. Common methods of estimating the
Water Residence Time focus on cross-correlation, parameter fitting and
non-parametric deconvolution methods. Here we propose a 1D full-deconvolution,
regularized, non-parametric inverse problem algorithm that enforces smoothness
and uses constraints of causality and positivity to estimate the Water
Residence Time curve. Compared to Bayesian non-parametric deconvolution
approaches, it has a fast runtime per test case; compared to the popular and
fast cross-correlation method, it produces a more precise Water Residence Time
curve even in the case of noisy measurements. The algorithm needs only one
regularization parameter to balance between smoothness of the Water Residence
Time and accuracy of the reconstruction. We propose an approach on how to
automatically find a suitable value of the regularization parameter from the
input data only. Tests on real data illustrate the potential of this method to
analyze hydrological datasets.
On the Basel Liquidity Formula for Elliptical Distributions
Date: 2018-03-20 00:00:00

A justification of the Basel liquidity formula for risk capital in the
trading book is given under the assumption that market risk-factor changes form
a Gaussian white noise process over 10-day time steps and changes to P&L are
linear in the risk-factor changes. A generalization of the formula is derived
under the more general assumption that risk-factor changes are multivariate
elliptical. It is shown that the Basel formula tends to be conservative when
the elliptical distributions are from the heavier-tailed generalized hyperbolic
family. As a by-product of the analysis a Fourier approach to calculating
expected shortfall for general symmetric loss distributions is developed.
Quantifying resilience to recurrent ecosystem disturbances using flow-kick dynamics
Date: 2018-03-20 00:00:00

Shifting ecosystem disturbance patterns due to climate change (e.g. storms,
droughts, wildfires) or direct human interference (e.g. harvests, nutrient
loading) highlight the importance of quantifying and strengthening the
resilience of desired ecological regimes. Although existing metrics capture
resilience to isolated shocks, gradual parameter changes, and continuous noise,
quantifying resilience to repeated, discrete disturbances requires novel
analytical tools. Here we introduce a flow-kick framework that quantifies
resilience to disturbances explicitly in terms of their magnitude and
frequency. We present a resilience boundary between disturbances that cause
either escape from a basin of attraction or stabilization within it, and use
the resilience boundary to build resilience metrics tailored to repeated,
discrete disturbances. The flow-kick model suggests that the
distance-to-threshold resilience metric overestimates resilience in the context
of repeated disturbances. It also reveals counterintuitive triggers for regime
shifts, such as increasing recovery times between disturbances, or increasing
disturbance magnitude and recovery times proportionately.
A note on the complexity of evolutionary dynamics in a classic consumer-resource model
Date: 2018-03-20 00:00:00

We study how the complexity of evolutionary dynamics in the classic MacArthur
consumer-resource model depends on resource uptake and utilization rates. The
traditional assumption in such models is that the utilization rate of the
consumer is proportional to the uptake rate. More generally, we show that if
these two rates are related through a power law (which includes the traditional
assumption as a special case), then the resulting evolutionary dynamics in the
consumer is necessarily a simple hill-climbing process leading to an
evolutionary equilibrium, regardless of the dimension of phenotype space. When
utilization and uptake rates are not related by a power law, more complex
evolutionary trajectories can occur, including the chaotic dynamics observed in
previous studies for high-dimensional phenotype spaces. These results draw
attention to the importance of distinguishing between utilization and uptake
rates in consumer-resource models.
Robust Beamforming for SWIPT System with Chance Constraints
Date: 2018-03-21 00:00:00

The robust beamforming problem in multiple-input single-output (MISO)
downlink networks of simultaneous wireless information and power transfer
(SWIPT) is studied in this paper. Adopting the time switching fashion to
perform energy harvesting and information decoding respectively, we aim at
maximizing the sum rate under imperfect channel state information (CSI) and the
chance constraints of users' harvested energy. In view of the fact that the
constraints for minimal harvested energy is not necessary to meet from time to
time, this paper adopts chance constraint to model it and uses the Bernstein
inequality to transform it into deterministic constraints equivalently.
Recognizing the maximum sum rate problem of imperfect CSI as nonconvex problem,
we transform it into finding the expectation of minimum mean square error
(MMSE) equivalently in this paper, and an alternative optimization (AO)
algorithm is proposed to decompose the optimization problem into two
sub-problems: the transmit beamformer design and the division of switching
time. The simulation results show the performance gains compared to non-robust
state of the art schemes.
Asymptotic Optimal Portfolio in Fast Mean-reverting Stochastic Environments
Date: 2019-01-29 00:00:00
Tasks: Portfolio Optimization

This paper studies the portfolio optimization problem when the investor's
utility is general and the return and volatility of the risky asset are fast
mean-reverting, which are important to capture the fast-time scale in the
modeling of stock price volatility. Motivated by the heuristic derivation in
[J.-P. Fouque, R. Sircar and T. Zariphopoulou, \emph{Mathematical Finance},
2016], we propose a zeroth order strategy, and show its asymptotic optimality
within a specific (smaller) family of admissible strategies under proper
assumptions. This optimality result is achieved by establishing a first order
approximation of the problem value associated to this proposed strategy using
singular perturbation method, and estimating the risk-tolerance functions. The
results are natural extensions of our previous work on portfolio optimization
in a slowly varying stochastic environment [J.-P. Fouque and R. Hu, \emph{SIAM
Journal on Control and Optimization}, 2017], and together they form a whole
picture of analyzing portfolio optimization in both fast and slow environments.
Mixed-timescale Per-group Hybrid Precoding for Multiuser Massive MIMO Systems
Date: 2018-03-21 00:00:00

Considering the expensive radio frequency (RF) chain, huge training overhead
and feedback burden issues in massive MIMO, in this letter, we propose a
mixed-timescale per-group hybrid precoding (MPHP) scheme under an adaptive
partially-connected RF precoding structure (PRPS), where the RF precoder is
implemented using an adaptive connection network (ACN) and M analog phase
shifters (APSs), where M is the number of antennas at the base station (BS).
Exploiting the mixed-time stage channel state information (CSI) structure, the
joint-design of ACN and APSs is formulated as a statistical
signal-to-leakage-and-noise ratio (SSLNR) maximization problem, and a heuristic
group RF precoding (GRFP) algorithm is proposed to provide a near-optimal
solution. Simulation results show that the proposed design advances at better
energy efficiency (EE) and lower hardware cost, CSI signaling overhead and
computational complexity than the conventional hybrid precoding (HP) schemes.
Statistical Properties and Variations of LOS MIMO Channels at Millimeter Wave Frequencies
Date: 2018-03-21 00:00:00

Measurement results for millimeter wave LOS MIMO systems are presented with a
focus on time variation and multipath propagation. Different system setups are
used, including 2x2 and 3x3 MIMO, and involving different synchronization
procedures and front-ends. Furthermore, different propagation scenarios are
evaluated, covering a wide area of applications. The results show that the LOS
component carries significantly more power than the NLOS components, and that
frequency selectivity from front-ends should be taken into account when
designing these high bandwidth systems. Frequency offsets and other phase
variations due to transmit and receive oscillator differences are treated as
part of the channel and thus, depending on the synchronization setup, the MIMO
system exhibits different time variations, particularly in the case of
independent local oscillators. It is also observed that these systems
experience significant non-trivial long-term variations in terms of amplitude
and phase.
Cross-Layer Energy Efficient Resource Allocation in PD-NOMA based H-CRANs: Implementation via GPU
Date: 2018-03-21 00:00:00
Tasks: GPU

In this paper, we propose a cross layer energy efficient resource allocation
and remote radio head (RRH) selection algorithm for heterogeneous traffic in
power domain - non-orthogonal multiple access (PD-NOMA) based heterogeneous
cloud radio access networks (H-CRANs). The main aim is to maximize the EE of
the elastic users subject to the average delay constraint of the streaming
users and the constraints, RRH selection, subcarrier, transmit power and
successive interference cancellation. The considered optimization problem is
non-convex, NP-hard and intractable. To solve this problem, we transform the
fractional objective function into a subtractive form. Then, we utilize
successive convex approximation approach. Moreover, in order to increase the
processing speed, we introduce a framework for accelerating the successive
convex approximation for low complexity with the Lagrangian method on graphics
processing unit. Furthermore, in order to show the optimality gap of the
proposed successive convex approximation approach, we solve the proposed
optimization problem by applying an optimal method based on the monotonic
optimization. Studying different scenarios show that by using both PD-NOMA
technique and H-CRAN, the system energy efficiency is improved.
Particle Filter for Randomly Delayed Measurements with Unknown Latency Probability
Date: 2018-03-21 00:00:00

This paper focuses on designing a particle filter for randomly delayed
measurements with an unknown latency probability. A generalized measurement
model is adopted which includes measurements that are delayed randomly by an
arbitrary but fixed maximum number of the steps, along with random packet
drops. Recursion equation for importance weights is derived under the presence
of random delays. Offline and online algorithms for identification of the
unknown latency parameter using the maximum likelihood criterion are proposed.
Further, this work explores the conditions which ensure the convergence of the
proposed particle filter. Finally, two numerical examples concerning problems
of non-stationary growth model and the bearing-only tracking are simulated to
show the effectiveness and superiority of the proposed filter.
An Experimental Study on Relative and Absolute Pose Graph Fusion for Vehicle Localization
Date: 2018-03-21 00:00:00

In this work, we research and evaluate multiple pose-graph fusion strategies
for vehicle localization. We focus on fusing a single absolute localization
system, i.e. automotive-grade Global Navigation Satellite System (GNSS) at 1
Hertz, with a single relative localization system, i.e. vehicle odometry at 25
Hertz. Our evaluation is based on 180 Km long vehicle trajectories that are
recorded in highway, urban and rural areas, and that are accompanied with
post-processed Real Time Kinematic GNSS as ground truth. The results exhibit a
significant reduction in the error's standard deviation by 18% but the bias in
the error is unchanged, when compared to non-fused GNSS. We show that the
underlying principle is the fact that errors in GNSS readings are highly
correlated in time. This causes a bias that cannot be compensated for by using
the relative localization information from the odometry, but it can reduce the
standard deviation of the error.
Contribution of Data Categories to Readmission Prediction Accuracy
Date: 2018-03-22 00:00:00
Tasks: Prediction, Readmission Prediction

Identification of patients at high risk for readmission could help reduce
morbidity and mortality as well as healthcare costs. Most of the existing
studies on readmission prediction did not compare the contribution of data
categories. In this study we analyzed relative contribution of 90,101 variables
across 398,884 admission records corresponding to 163,468 patients, including
patient demographics, historical hospitalization information, discharge
disposition, diagnoses, procedures, medications and laboratory test results. We
established an interpretable readmission prediction model based on Logistic
Regression in scikit-learn, and added the available variables to the model one
by one in order to analyze the influences of individual data categories on
readmission prediction accuracy. Diagnosis related groups (c-statistic
increment of 0.0933) and discharge disposition (c-statistic increment of
0.0269) were the strongest contributors to model accuracy. Additionally, we
also identified the top ten contributing variables in every data category.