pwc-archive/papers-with-abstracts huggingface dataset:
Robust OFDM integrated radar and communications waveform design based on information theory
Date: 2019-05-22 00:00:00
Tasks: Philosophy

An integrated radar and communications system (IRCS) where a monostatic radar
transceiver is employed for target classification while simultaneously used as
a communications transmitter is considered. The radar combined
propagation-target response (joint response of the radar propagation channel
and target) and communications channel response are generally frequency
selective but the corresponding frequency response functions are not exactly
known. In particular, these frequency response functions are only known to lie
in an uncertainty class. To ensure the IRCS simultaneously provides acceptable
target classification performance and communications rate, a robust orthogonal
frequency division multiplexing (OFDM) integrated radar and communications
waveform (IRCW) design method is proposed. The approach finds a waveform that
simultaneously provides a sufficiently large weighted sum of the communications
data information rate (DIR) and the conditional mutual information (MI) between
the observed signal and the radar target over the entire uncertainty class.
First, the conditional MI and DIR based on the integrated OFDM radar and
communications waveform are derived. Then, a robust OFDM IRCW optimization
problem based on the minimax design philosophy is developed such that
closed-form solution is derived. Finally, several numerical results are
presented to demonstrate the effectiveness of the proposed method.
Approximating $(k,\ell)$-center clustering for curves
Authors: Buchin Kevin, Driemel Anne, Gudmundsson Joachim, Horton Michael, Kostitsyna Irina, Löffler Maarten, Struijs Martijn
Date: 2018-07-20 00:00:00
Tasks: Clustering

The Euclidean $k$-center problem is a classical problem that has been
extensively studied in computer science. Given a set $\mathcal{G}$ of $n$
points in Euclidean space, the problem is to determine a set $\mathcal{C}$ of
$k$ centers (not necessarily part of $\mathcal{G}$) such that the maximum
distance between a point in $\mathcal{G}$ and its nearest neighbor in
$\mathcal{C}$ is minimized. In this paper we study the corresponding
$(k,\ell)$-center problem for polygonal curves under the Fr\'echet distance,
that is, given a set $\mathcal{G}$ of $n$ polygonal curves in $\mathbb{R}^d$,
each of complexity $m$, determine a set $\mathcal{C}$ of $k$ polygonal curves
in $\mathbb{R}^d$, each of complexity $\ell$, such that the maximum Fr\'echet
distance of a curve in $\mathcal{G}$ to its closest curve in $\mathcal{C}$ is
minimized. In this paper, we substantially extend and improve the known
approximation bounds for curves in dimension $2$ and higher. We show that, if
$\ell$ is part of the input, then there is no polynomial-time approximation
scheme unless $\mathsf{P}=\mathsf{NP}$. Our constructions yield different
bounds for one and two-dimensional curves and the discrete and continuous
Fr\'echet distance. In the case of the discrete Fr\'echet distance on
two-dimensional curves, we show hardness of approximation within a factor close
to $2.598$. This result also holds when $k=1$, and the $\mathsf{NP}$-hardness
extends to the case that $\ell=\infty$, i.e., for the problem of computing the
minimum-enclosing ball under the Fr\'echet distance. Finally, we observe that a
careful adaptation of Gonzalez' algorithm in combination with a curve
simplification yields a $3$-approximation in any dimension, provided that an
optimal simplification can be computed exactly. We conclude that our
approximation bounds are close to being tight.
Normative atlases of neuroelectric brain activity and connectivity from a large human cohort
Date: 2018-11-17 00:00:00

Magnetoencephalographic (MEG) recordings from a large normative cohort (n =
619) were processed to extract measures of regional neuroelectric activity. The
overall objective of the effort was to use these measures to identify normative
human neuroelectric brain function. The aims were (a) to identify and measure
the values and range of those neuroelectric properties which are common to the
cohort, (b) to identify and measure the values and range of those neuroelectric
properties which distinguish one individual from another, and (c) to identify
relationships of the measures to properties of the individual, e.g. sex,
biological age, and sleep symptoms. It is hoped that comparison of the
resultant established norms to measures from recordings of symptomatic
individuals will enable advances is our understanding of pathology.
  MEG recordings during resting and task conditions were provided by The
Cambridge (UK) Centre for Ageing and Neuroscience Stage 2 cohort study. Referee
consensus processing was used to localize and validate neuroelectric currents,
p < 10-12 for each, p < 10-4 for each when corrected for multiple comparisons.
  Comparisons of regional activity and connectivity within-subjects produced
profuse reliable measures detailing differences between individuals, p < 10-8
for each comparison, p < 0.005 for each when corrected for a total of 5 x 105
comparisons. Cohort-wide regional comparisons (p < 10-8 for each) produced
profuse measures which were common to the preponderance of individuals,
detailing normative commonalities in brain function. Comparisons of regional
gray matter (cellular) vs white matter (communication fibers) activity produced
robust differences both cohort-wide and for each individual. These results
validate the high spatial resolution of the results and establish the
unprecedented ability to obtain neuroelectric measures from the white matter.
Is Information in the Brain Represented in Continuous or Discrete Form?
Date: 2020-09-16 00:00:00
Tasks: Form

The question of continuous-versus-discrete information representation in the
brain is a fundamental yet unresolved question. Historically, most analyses
assume a continuous representation without considering the discrete
alternative. Our work explores the plausibility of both, answering the question
from a communications systems engineering perspective. Using Shannon's
communications theory, we posit that information in the brain is represented in
discrete form. We address this hypothesis using 2 approaches. First, we
identify the fundamental communication requirements of the brain. Second, we
estimate the symbol error probability and channel capacity for a continuous
information representation. Our work concludes that information cannot be
communicated and represented reliably in the brain using a continuous
representation - it has to be in a discrete form. This is a major demarcation
from conventional and current wisdom. We apply this discrete result to the 4
major neural coding hypotheses, and illustrate the use of discrete ISI neural
coding in analyzing electrophysiology experimental data. We further posit and
illustrate a plausible direct link between Weber's Law and discrete neural
coding. We end by outlining a number of key research questions on discrete
neural coding.
Optimizing Native Ion Mobility Q-TOF in Helium and Nitrogen for Very Fragile Noncovalent Interactions
Date: 2018-07-16 00:00:00

The meaningful comparison of ion mobility (IM) results and of collision cross
section (CCS) values on different platforms is a prerequisite for using CCS for
identification or structural assignment. The amount of internal energy imparted
to the ions prior to the ion mobility cell is a source of experimental
variation. Here we investigated the effects of virtually all tuning parameters
of the Agilent 6560 IM-Q-TOF on the arrival time distributions of Ubiquitin7+,
and found conditions in which the native state prevails. We will discuss the
effects of solvent evaporation conditions in the source, in the entire pre-IM
DC voltage gradient, and with the funnel RF amplitudes, and will also report on
ubiquitin7+ conformations in different solvents, including native supercharging
conditions. Collision-induced unfolding (CIU) can be conveniently provoked in
two distinct regions: behind the source capillary (by changing the fragmentor
voltage) and in the trapping funnel (by changing the trap entrance grid delta
voltage). The softness of the instrumental conditions were then optimized with
the benchmark DNA G-quadruplex [(dG4T4G4)2.(NH4+)3-8H]5-, for which ion
activation results in ammonia loss. To reduce the ion internal energy and
obtain the intact 3-NH4+ complex, we reduced the post-IM voltage gradient, but
this resulted in a lower IM resolving power due to increased diffusion behind
the drift tube. The article thus describes the various trade-offs between ion
activation, ion transmission, and ion mobility performance for native MS of
very fragile structures.
Asynchronous Multiple Access in Optical Wireless Scattering Communication: Achievable Transmission Rates and Receiver Design
Date: 2019-01-22 00:00:00

We investigate the asynchronous multiple user access communication in optical
wireless scattering communication, where different users transmit signals
without perfect alignment in the time domain. Firstly, we characterize the
received signal based on hidden markov model (HMM) such that the misalignment
among different users can be characterized by the state transition. Then, we
investigate the achievable rates based on that of the HMM and obtain the
approximated solution using Monte Carlo method. We propose the channel
estimation based on expectation-maximization (EM) algorithm. Furthermore, we
adopt Viterbi and Bahl-Cocke-Jelinek-Raviv (BCJR) algorithms for joint
iterative multi-user decoding. Numerical and experimental results illustrate
the performance of proposed channel estimation, joint detection and decoding.
It is seen from the experimental results that the proposed approaches perform
close to the simulation results.
Target Apps Selection: Towards a Unified Search Framework for Mobile Devices
Authors: Aliannejadi Mohammad, Zamani Hamed, Crestani Fabio, Croft W. Bruce
Date: 2018-07-13 00:00:00
Tasks: Retrieval

With the recent growth of conversational systems and intelligent assistants
such as Apple Siri and Google Assistant, mobile devices are becoming even more
pervasive in our lives. As a consequence, users are getting engaged with the
mobile apps and frequently search for an information need in their apps.
However, users cannot search within their apps through their intelligent
assistants. This requires a unified mobile search framework that identifies the
target app(s) for the user's query, submits the query to the app(s), and
presents the results to the user. In this paper, we take the first step forward
towards developing unified mobile search. In more detail, we introduce and
study the task of target apps selection, which has various potential real-world
applications. To this aim, we analyze attributes of search queries as well as
user behaviors, while searching with different mobile apps. The analyses are
done based on thousands of queries that we collected through crowdsourcing. We
finally study the performance of state-of-the-art retrieval models for this
task and propose two simple yet effective neural models that significantly
outperform the baselines. Our neural approaches are based on learning
high-dimensional representations for mobile apps. Our analyses and experiments
suggest specific future directions in this research area.
Tensor-Based Channel Estimation for Dual-Polarized Massive MIMO Systems
Date: 2018-10-26 00:00:00
Tasks: Tensor Decomposition

The 3GPP suggests to combine dual polarized (DP) antenna arrays with the
double directional (DD) channel model for downlink channel estimation. This
combination strikes a good balance between high-capacity communications and
parsimonious channel modeling, and also brings limited feedback schemes for
downlink channel state information within reach---since such channel can be
fully characterized by several key parameters. However, most existing channel
estimation work under the DD model has not yet considered DP arrays, perhaps
because of the complex array manifold and the resulting difficulty in algorithm
design. In this paper, we first reveal that the DD channel with DP arrays at
the transmitter and receiver can be naturally modeled as a low-rank tensor, and
thus the key parameters of the channel can be effectively estimated via tensor
decomposition algorithms.
  On the theory side, we show that the DD-DP parameters are identifiable under
very mild conditions, by leveraging identifiability of low-rank tensors.
Furthermore, a compressed tensor decomposition algorithm is developed for
alleviating the downlink training overhead. We show that, by using judiciously
designed pilot structure, the channel parameters are still guaranteed to be
identified via the compressed tensor decomposition formulation even when the
size of the pilot sequence is much smaller than what is needed for conventional
channel identification methods, such as linear least squares and matched
filtering.
  Numerical simulations are presented to showcase the effectiveness of the
proposed methods.
A Markovian genomic concatenation model guided by persymmetric matrices
Date: 2019-11-26 00:00:00

The aim of this work is to provide a rigorous mathematical analysis of a
stochastic concatenation model presented by Sobottka and Hart (2011) which
allows approximation of the first-order stochastic structure in bacterial DNA
by means of a stationary Markov chain. Two probabilistic constructions that
rigorously formalize the model are presented. Necessary and sufficient
conditions for a Markov chain to be generated by the model are given, as well
as the theoretical background needed for designing new algorithms for
statistical analyses of real bacterial genomes. It is shown that the model
encompasses the Markov chains satisfying intra-strand parity, a property
observed in most DNA sequences.
An Axiomatic Analysis of Diversity Evaluation Metrics: Introducing the Rank-Biased Utility Metric
Authors: Amigó Enrique, Spina Damiano, Carrillo-de-Albornoz Jorge
Date: 2018-08-19 00:00:00
Tasks: Diversity, Retrieval

Many evaluation metrics have been defined to evaluate the effectiveness
ad-hoc retrieval and search result diversification systems. However, it is
often unclear which evaluation metric should be used to analyze the performance
of retrieval systems given a specific task. Axiomatic analysis is an
informative mechanism to understand the fundamentals of metrics and their
suitability for particular scenarios. In this paper, we define a
constraint-based axiomatic framework to study the suitability of existing
metrics in search result diversification scenarios. The analysis informed the
definition of Rank-Biased Utility (RBU) -- an adaptation of the well-known
Rank-Biased Precision metric -- that takes into account redundancy and the user
effort associated to the inspection of documents in the ranking. Our
experiments over standard diversity evaluation campaigns show that the proposed
metric captures quality criteria reflected by different metrics, being suitable
in the absence of knowledge about particular features of the scenario under
study.
Robust Design of Power Minimizing Symbol-Level Precoder under Channel Uncertainty
Date: 2018-08-12 00:00:00
Tasks: Robust Design

In this paper, we investigate the downlink transmission of a multiuser
multiple-input single-output (MISO) channel under a symbol-level precoding
(SLP) scheme, having imperfect channel knowledge at the transmitter. In
defining the SLP problem, a general category of constructive interference
regions (CIR) called distance preserving CIR (DPCIR) is adopted. In particular,
we are interested in the robust SLP design minimizing the total transmit power
while satisfying the users' quality-of-service (QoS) requirements. We consider
two common models for the channel uncertainty region, namely, norm-bounded
spherical and stochastic. For the spherical uncertainty model, a worst-case
robust precoder is proposed, while for the stochastic uncertainties, we define
a convex optimization problem with probabilistic constraints. We simulate the
performance of the proposed robust approaches, and compare them with the
existing methods. Through the simulation results, we also show that there is an
essential trade-off between the two robust approaches.
Dual-Polarization FBMC for Improved Performance in Wireless Communication Systems
Date: 2018-08-17 00:00:00

Filter bank multi-carrier (FBMC) offers superior spectral properties compared
to cyclic-prefix orthogonal frequency-division multiplexing (CP-OFDM), at the
cost of an inherent shortcoming in dispersive channels called intrinsic
imaginary interference. In this paper we propose a new FBMC based communication
system using two orthogonal polarizations for wireless communication systems:
dual-polarization FBMC (DP-FBMC). Using this system we can significantly
suppress the FBMC intrinsic interference. Therefore in DP-FBMC all the
multicarrier techniques used in CP-OFDM systems such as channel equalization,
etc., should be applicable without using the complex processing methods
required for conventional FBMC. DP-FBMC also has other interesting advantages
over CP-OFDM and FBMC: it is more robust in highly dispersive channels, and
also to receiver carrier frequency offset (CFO) and timing offset (TO). In our
DP-FBMC system we propose three different structures based on different
multiplexing techniques. We show that compared to conventional FBMC, one of
these DP-FBMC structures has equivalent complexity and equipment requirements.
We compare DP-FBMC with other systems through simulations. According to our
results DP-FBMC has potential as a promising candidate for future wireless
communication networks.
Optimal make-take fees for market making regulation
Authors: Omar El Euch, Thibaut Mastrolia, Mathieu Rosenbaum, Nizar Touzi
Date: 2018-05-07 00:00:00

We consider an exchange who wishes to set suitable make-take fees to attract liquidity on its platform. Using a principal-agent approach, we are able to describe in quasi-explicit form the optimal contract to propose to a market maker. This contract depends essentially on the market maker inventory trajectory and on the volatility of the asset. We also provide the optimal quotes that should be displayed by the market maker. The simplicity of our formulas allows us to analyze in details the effects of optimal contracting with an exchange, compared to a situation without contract. We show in particular that it leads to higher quality liquidity and lower trading costs for investors.
Fundamentals of Multi-Numerology 5G New Radio
Date: 2019-06-13 00:00:00

The physical layer of 5G cellular communications systems is designed to
achieve better flexibility in an effort to support diverse services and user
requirements. OFDM waveform parameters are enriched with flexible
multi-numerology structures. This paper describes the differences between Long
Term Evolution (LTE) systems and new radio (NR) from the flexibility
perspective. Research opportunities for multi-numerology systems are presented
in a structured manner. Finally, inter-numerology interference (INI) results as
a function of guard allocation and multi-numerology parameters are obtained
through simulation.
Modeling, Simulation and Fairness Analysis of Wi-Fi and Unlicensed LTE Coexistence
Date: 2018-04-29 00:00:00
Tasks: Fairness

Coexistence of small-cell LTE and Wi-Fi networks in unlicensed bands at $5$
GHz is a topic of active interest, primarily driven by industry groups
affiliated with the two (cellular and Wi-Fi) segments. A notable alternative to
the 3GPP Rel. 13 defined LTE-Licensed Assisted Access (LTE-LAA) mechanism for
coexistence is the unlicensed LTE (LTE-U) Forum \cite{lteuforum} that
prescribed Carrier Sense Adaptive Transmission (CSAT) whereby LTE utilizes the
unlicensed band as a supplemental downlink unlicensed carrier (to enhance
downlink data rate) to normal operation using licensed spectrum. In this work,
we provide a new analytical model for performance analysis of unlicensed LTE
with fixed duty cycling (LTE-DC) in coexistence with Wi-Fi. Further, the
analytical results are cross-validated with ns-3 (www.nsnam.org) based
simulation results using a newly developed coexistence stack. Thereafter,
notions of {\em fair coexistence} are investigated that can be achieved by
tuning the LTE duty cycle. The results show that as the number of Wi-Fi nodes
increases, the Wi-Fi network in coexistence with LTE-DC with 0.5 duty cycling
achieves a higher throughput than with an identical Wi-Fi network.
Reconciling cooperation, biodiversity and stability in complex ecological communities
Date: 2018-05-16 00:00:00

Empirical observations show that ecological communities can have a huge
number of coexisting species, also with few or limited number of resources.
These ecosystems are characterized by multiple type of interactions, in
particular displaying cooperative behaviors. However, standard modeling of
population dynamics based on Lotka-Volterra type of equations predicts that
ecosystem stability should decrease as the number of species in the community
increases and that cooperative systems are less stable than communities with
only competitive and/or exploitative interactions. Here we propose a stochastic
model of population dynamics, which includes exploitative interactions as well
as cooperative interactions induced by cross-feeding. The model is exactly
solved and we obtain results for relevant macro-ecological patterns, such as
species abundance distributions and correlation functions. In the large system
size limit, any number of species can coexist for a very general class of
interaction networks and stability increases as the number of species grows.
For pure mutualistic/commensalistic interactions we determine the topological
properties of the network that guarantee species coexistence. We also show that
the stationary state is globally stable and that inferring species interactions
through species abundance correlation analysis may be misleading. Our
theoretical approach thus show that appropriate models of cooperation naturally
leads to a solution of the long-standing question about complexity-stability
paradox and on how highly biodiverse communities can coexist.
A quick guide for student-driven community genome annotation
Date: 2018-10-16 00:00:00

High quality gene models are necessary to expand the molecular and genetic
tools available for a target organism, but these are available for only a
handful of model organisms that have undergone extensive curation and
experimental validation over the course of many years. The majority of gene
models present in biological databases today have been identified in draft
genome assemblies using automated annotation pipelines that are frequently
based on orthologs from distantly related model organisms. Manual curation is
time consuming and often requires substantial expertise, but is instrumental in
improving gene model structure and identification. Manual annotation may seem
to be a daunting and cost-prohibitive task for small research communities but
involving undergraduates in community genome annotation consortiums can be
mutually beneficial for both education and improved genomic resources. We
outline a workflow for efficient manual annotation driven by a team of
primarily undergraduate annotators. This model can be scaled to large teams and
includes quality control processes through incremental evaluation. Moreover, it
gives students an opportunity to increase their understanding of genome biology
and to participate in scientific research in collaboration with peers and
senior researchers at multiple institutions.